Job Title: Applied AI Platform Engineer-DATA ENGINEER - Software Specialist Engineer II Company: Deloitte Job Category: Machine Learning Roles & Responsibilities: Role Overview: As an Applied AI Platform Engineer II*, you will actively engage in your engineering craft, taking a hands\-on approach to building the platforms, tooling, accelerators, and frameworks that other engineering teams build on. Your expertise will be pivotal in delivering platform capabilities that delight the engineers who depend on them, while driving tangible leverage and value across Deloitte’s AI engineering investments. You will leverage your extensive engineering craftsmanship across platform engineering, distributed systems, and modern AI/ML and Data infrastructure, consistently demonstrating your strong track record in delivering high\-quality, reusable, outcome\-focused solutions. The ideal candidate will be a dependable team player, collaborating with cross\-functional teams to design, build, and operate the enabling layer for AI engineering at scale. Key Responsibilities: * Embrace and drive a culture of accountability for engineering\-leverage and adoption outcomes. Build platform capabilities that solve recurring problems once, well, for many teams—reducing per\-team build and operate toil while ensuring consistency and compliance by default through high\-quality, lean designs and implementations. * Serve as the technical advocate for the platform as a product, ensuring capability integrity, feasibility, and alignment with the needs of the engineering teams who consume it. Lead requirement discovery with consuming teams, component design of platform services, frameworks, and the AI control plane, and their development, testing, integration, and support. * Maintain accountability for the integrity of the platform architecture and for the enterprise tech\-stack conformance baseline that engineering teams build against. Manage platform dependencies, code design, implementation, the data and policy\-as\-code enforcement layers, and the OpenTelemetry\-based instrumentation substrate—building capabilities that are operable, instrumented, performant, and drift\-resistant by design, to the production standards set by SRE. Stay hands\-on, self\-driven, and continuously learn new approaches, languages, and frameworks. Create technical specifications, codify recurring patterns into reusable components and golden paths, and write high\-quality, supportable, scalable code to ensure all platform KPIs (adoption, reliability\-by\-design, and developer experience) are met or exceeded. Demonstrate collaborative skills to work effectively with diverse teams. * Develop lean platform capabilities through rapid, inexpensive experimentation to solve the real needs of consuming engineering teams. Engage with those teams before, during, and after delivery to ensure the right capability is delivered at the right time—and adopted, not shelved. * Adopt a mindset that favors action and evidence over extensive planning. Utilize a leaning\-forward approach to navigate complexity and uncertainty, delivering platform capabilities as lean, adoption\-validated increments rather than big\-bang builds, and keeping them supportable and maintainable. * Work collaboratively with empowered, cross\-functional partners: engineering, SRE, security and risk, data governance, and engineering leadership and architecture. Integrate their constraints into the paved roads so that the secure, compliant, and reliable path is the easy path. Deliver capabilities that are admissible\-by\-design and submit them for admission, co\-defining service\-level objectives with SRE, who set production standards and own the admission decision. Foster a collaborative environment that enhances team synergy and innovation. * Possess expertise in platform engineering and modern AI/ML infrastructure—internal developer platforms, MLOps/LLMOps, model serving, retrieval and vector infrastructure, eval and observability tooling, policy\-as\-code, container orchestration, IaC, and CI/CD at platform scale—including AI and Agentic SSDLC to deliver self\-service, governed capabilities with full automation from discovery to production to operations and all quality checks through the SSDLC lifecycle. Strive to be a role model, leveraging these techniques to optimize platform solutioning and delivery. Demonstrate strong understanding of the full lifecycle of platform and product development, focusing on continuous improvement and learning. * Quickly acquire domain knowledge of the enterprise data estate and the AI use\-case patterns the platform must serve. Translate the needs of engineering teams, reference architectures, and governance requirements into reusable frameworks, the data platform, and governance\-as\-code enforcement. Be a valuable, flexible, and dedicated team member, supportive of teammates, and focused on quality and tech debt payoff. * Exhibit exceptional communication skills, capable of articulating complex technical concepts clearly and compellingly. Inspire and influence teammates and product teams through well\-structured arguments and trade\-offs supported by evidence. Create coherent narratives that align technical solutions with business objectives. * Engage and collaborate with product engineering teams at all organizational levels, including customers as needed. Build and maintain constructive relationships, fostering a culture of co\-creation and shared momentum towards achieving product goals. Align diverse perspectives and drive consensus to create feasible solutions. The team: US Deloitte Technology Product Engineering has modernized software and product delivery, creating a scalable, cost\-effective model that focuses on value/outcomes that leverages a progressive and responsive talent structure. As Deloitte’s primary internal development team, Product Engineering delivers innovative digital solutions to businesses, service lines, and internal operations with proven bottom\-line results and outcomes. It helps power Deloitte’s success. It is the engine that drives Deloitte, serving many of the world’s largest, most respected companies. We develop and deploy cutting\-edge internal and go\-to\-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence. Our inclusive culture empowers our people to be who they are, contribute their unique perspectives, and make a difference individually and collectively. It enables us to leverage different ways of thinking, ideas and perspectives, and bring more creativity and innovation to help solve our clients’ most complex challenges. This makes Deloitte one of the most rewarding places to work. Professional development At Deloitte, professionals have the opportunity to work with some of the best and discover what works best for them. Here, we prioritize professional growth, offering diverse learning and networking opportunities to help accelerate careers and enhance leadership skills. Our state\-of\-the\-art DU: The Leadership Center in India, located in Hyderabad, represents a tangible symbol of our commitment to the holistic growth and development of our people. Explore DU: The Leadership Center in India. Benefits to help you thrive Work Location: Karnataka, India Availability: Full time

Job Title: Senior Data Scientist- Finance & Spend, Data Labs Company: SAP Job Category: Machine Learning Roles & Responsibilities: * Design and maintain enterprise ontologies and semantic models that give AI agents accurate, grounded understanding of SAP and connected business landscapes harmonizing data from SAP, Salesforce, Workday, ServiceNow, MES/IoT systems, and external providers into unified semantic layers. * Build AI capabilities including RAG pipelines, embeddings, vector databases, and enterprise knowledge grounding that make SAP's agents accurate and reliable in production. * Develop AI capabilities including generative AI and LLM\-based solutions using enterprise business data, knowledge graphs, business process intelligence, and other structured and unstructured data assets. * Leverage SAP's deep data and process context including SAP data models, metadata structures, and business process semantics across Order\-to\-Cash, Procure\-to\-Pay, Record\-to\-Report, and Plan\-to\-Produce to ground AI solutions in real enterprise reality. * Work with cloud and data platforms including Databricks, SAP Datasphere, SAP HANA Cloud, AWS, Azure, and GCP to support reliable, scalable AI workflows. * Partner across product, engineering, business, and customer\-facing teams to translate ambiguous business challenges into concrete AI solutions from concept through deployment and continuous improvement. * Apply machine learning, deep learning, and statistical modeling to develop and evaluate AI solutions using real\-world enterprise datasets. Bring out your best SAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively. Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end\-to\-end business application software and related services for database, analytics, intelligent technologies, and experience management. As a cloud company with two hundred million users and more than one hundred thousand employees worldwide, we are purpose\-driven and future\-focused, with a highly collaborative team ethic and commitment to personal development. Whether connecting global industries, people, or platforms, we help ensure every challenge gets the solution it deserves. At SAP, you can bring out your best. For SAP employees: Only permanent roles are eligible for the SAP Employee Referral Program, according to the eligibility rules set in the SAP Referral Policy. Specific conditions may apply for roles in Vocational Training. Requisition ID: 459702 \| Work Area: Software\-Design and Development \| Expected Travel: 0 \- 10% \| Career Status: Professional \| Employment Type: Regular Full Time \| Additional Locations: Work Location: Bengaluru, Karnataka, India Availability: Full time

Job Title: Software Development Engineer II (Machine Learning) | NR-2026-0229 Company: Media.net Job Category: Machine Learning Roles & Responsibilities: Media.net is a leading global ad tech company, building innovative products and solutions for advertisers and publishers. Media.net creates the most transparent and efficient path for ad budgets to become publisher revenue, while delivering meaningful value to advertisers, publishers, app developers, and end users across the open web. We are one of the world’s largest independent contextual advertising businesses, with one of the industry’s most comprehensive advertising technology portfolios. Media.net powers major publishers and ad\-tech platforms across formats, including display, video, mobile, native, search, and local. Our platform manages high\-quality ad supply across 500,000\+ websites and is licensed by the biggest publishers, ad networks, and technology partners worldwide. Beyond our core advertising business, Media.net also operates at scale in performance\-driven consumer acquisition, app development and distribution, and strategic technology investments. These efforts are supported by one of the world’s largest independent software development engines, enabling us to innovate rapidly and build products used across global markets. Role Overview As an SDE II – Machine Learning, you will be a core contributor in designing, building, and scaling ML\-driven systems that power our real\-time ad platforms. You'll be responsible for full\-stack ML development—from data engineering and model development to scalable deployment—working closely with product, data science, and engineering teams. · Flexible work hours, modern office spaces, and supportive teams. Work Location: Bengaluru, Karnataka, India Availability: Full time

Job Title: AI ML Developer Company: Scoutit Job Category: Machine Learning Roles & Responsibilities: We're looking for AI ML Developers ! Responsibilities : * Design, develop, train, and optimize Machine Learning and Deep Learning models. * Analyze structured and unstructured datasets to identify business insights and opportunities. * Build and maintain data pipelines for model training and inference. * Develop AI solutions using NLP, Computer Vision, Recommendation Systems, or Predictive Analytics. * Deploy ML models using cloud platforms and MLOps best practices. * Perform feature engineering, model evaluation, hyperparameter tuning, and performance optimization. * Collaborate with Data Scientists, Software Engineers, and business stakeholders. * Monitor model performance and retrain models as required. * Document model architecture, experiments, and deployment processes * Be a team player and work across teams. ( Note: Relevant applicants will receive an email requesting additional information as part of the next stage. The application process will be completed directly on the team's designated platform, and all subsequent communication and decisions regarding the opportunity are managed by the respective hiring team.) Work Location: Bengaluru, Karnataka, India Availability: Full time

Job Title: Machine Learning Engineer (Robotics/ Physical AI) Company: PeopleGene Job Category: Machine Learning Roles & Responsibilities: About the role: * Build training data to operate on physical robotic platforms. * Own the full machine learning lifecycle—from data collection and custom architecture design to edge deployment, simulation\-to\-real (sim\-to\-real) transfer, and continuous hardware optimization. * Design, train, and evaluate deep learning, computer vision, and multimodal models (e.g., Vision\-Language\-Action or VLA systems) for robotic perception, reasoning, and manipulation. * Apply synthetic data, domain randomization, imitation learning, and reinforcement learning within simulation environments before transferring policies to physical robots. * Optimize, quantize, and compile ML models to run with low latency on edge compute hardware, sensors, and embedded robotic platforms. * Build and maintain scalable data ingestion, labeling, automated testing, and MLOps/monitoring pipelines for real\-world operational data. * Work side\-by\-side with mechanical, electrical, controls, and software engineers to integrate AI models into safe, reliable physical machines. Work Location: Bengaluru, Karnataka, India Availability: Full time

Job Title: AI/ML Engineer Company: Solventum Job Category: Machine Learning Roles & Responsibilities: At Solventum, we improve lives by helping healthcare professionals do their best work. Join a team using innovation and insight to make a real impact on the future of healthcare. All roles listed are with Solventum, and we’re committed to protecting your personal information—learn more in our Privacy Policy: https://www.solventum.com/en\-us/home/legal/website\-privacy\-statement/applicant\-privacy/ Job Description AI/ ML Engineer (Solventum) 3M Health Care is now Solventum At Solventum, we enable better, smarter, safer healthcare to improve lives. As a new company with a long legacy of creating breakthrough solutions for our customers’ toughest challenges, we pioneer game\-changing innovations at the intersection of health, material and data science that change patients' lives for the better while enabling healthcare professionals to perform at their best. Because people, and their wellbeing, are at the heart of every scientific advancement we pursue. We partner closely with the brightest minds in healthcare to ensure that every solution we create melds the latest technology with compassion and empathy. Because at Solventum, we never stop solving for you. The Impact You’ll Make in this Role As An AI/ML Engineer, You Will Have The Opportunity To Tap Into Your Curiosity And Collaborate With Some Of The Most Innovative And Diverse People Around The World. Here, You Will Make An Impact By * Design, develop, and implement AI/ML solutions to solve business problems, contributing to projects from proof of concept and pilot through production deployment. * Build and apply both traditional machine learning models and modern AI techniques, including large language models (LLMs), generative AI, retrieval\-augmented generation (RAG), and agentic AI systems. * Collaborate with senior engineers, product managers, data scientists, and business stakeholders to refine project scope, technical approach, success metrics, and deployment requirements. * Contribute to building scalable and maintainable AI systems with a focus on accuracy, robustness, fairness, and explainability, adhering to responsible AI principles. * Apply model evaluation frameworks to assess performance, generalization, bias, and resilience to edge cases or adversarial inputs. * Support the transition of AI prototypes into production\-ready systems by partnering with platform and engineering teams on deployment, monitoring, and lifecycle management. * Contribute to documentation, governance, and compliance processes to meet enterprise and regulatory standards, especially in healthcare and other regulated environments. Work location: * Hybrid Solventum is committed to maintaining the highest standards of integrity and professionalism in our recruitment process. Applicants must remain alert to fraudulent job postings and recruitment schemes that falsely claim to represent Solventum and seek to exploit job seekers. Work Location: Bengaluru, Karnataka, India Availability: Full time

Job Title: ML Engineer I Company: UST Job Category: Machine Learning Roles & Responsibilities: Role description UST is seeking an experienced AI \& Python Automation Engineer with expertise in Python development, Generative AI, Test Data Management (TDM), workflow automation, and enterprise application modernization. The ideal candidate will be responsible for developing intelligent automation solutions, integrating AI\-powered capabilities, and driving innovation through modern technologies that improve operational efficiency and user experience. As an AI \& Python Automation Engineer, you will design, develop, and implement AI\-enabled solutions that automate business processes, enhance Test Data Management capabilities, and accelerate digital transformation initiatives. You will work closely with business stakeholders, product teams, architects, and engineers to build scalable applications leveraging Python, Large Language Models (LLMs), automation frameworks, and cloud\-native technologies. ### Key Roles \& Responsibilities * Design, develop, and maintain Python\-based automation solutions to streamline operational processes and improve efficiency. * Build AI\-powered applications and intelligent workflows using Generative AI technologies and Large Language Models (LLMs). * Develop and integrate automation frameworks that reduce manual effort and improve business productivity. * Collaborate with business stakeholders to gather requirements and translate them into scalable digital solutions. * Design and implement REST APIs and backend services using Python\-based frameworks such as FastAPI and Flask. * Develop AI\-driven solutions for intelligent automation, data processing, content generation, and workflow optimization. * Support Test Data Management (TDM) modernization initiatives through automation and AI adoption. * Implement data masking, synthetic data generation, and data provisioning solutions. * Utilize prompt engineering techniques to optimize Generative AI model performance and business outcomes. * Integrate AI and automation capabilities into enterprise applications and business processes. * Monitor application performance, analyze user feedback, and continuously enhance solutions. * Ensure compliance with security, privacy, accessibility, and enterprise governance standards. * Troubleshoot automation, application, integration, and AI model issues. * Participate in proof\-of\-concepts (POCs), innovation programs, and digital transformation initiatives. * Collaborate with cross\-functional teams in Agile environments to deliver reliable, scalable solutions. * Evaluate emerging AI technologies and recommend innovative approaches to improve platform capabilities. Required Skills ### Programming \& Development * Python * FastAPI * Flask * REST APIs * SQLAlchemy * Microservices Development * Workflow Automation * Backend Development * Generative AI * Large Language Models (LLMs) * Prompt Engineering * AI Solution Development * LangChain * AI Agent Development * Scikit\-learn * TensorFlow * PyTorch * AI/ML Integration ### Test Data Management (TDM) Skills * Python * Generative AI * Artificial Intelligence * Prompt Engineering * FastAPI * Flask * LangChain * Automation * Test Data Management (TDM) * Data Masking * Synthetic Data Generation * REST APIs * Data Processing * SQL * Machine Learning We honor our commitments and act with responsibility in all our relationships. UST reserves the right to periodically redefine your roles and responsibilities based on organizational requirements and/or your performance. * To support and promote the values of UST. * Comply with all Company policies and procedures. Python, Generative AI, Test Data Management, Workflow Automation, REST, FastAPI, Flask, Pandas, NumPy, SQLAlchemy, MySQL Work Location: Karnataka, India Availability: Full time

Job Title: Lead Software Engineer - Cloud Architecture Company: JPMorganChase Job Category: Machine Learning Roles & Responsibilities: JOB DESCRIPTION As a Lead Software Engineer at JPMorganChase within the Securities Services Engineering and Architecture team, you will deliver high\-quality architecture solutions for modern cloud\-based applications. You will work closely with technology teams across multiple product areas, providing subject matter expertise and supporting proofs of concept. Your deep technical knowledge and problem\-solving skills will help design and operate secure, efficient cloud\-native applications across private and public cloud environments. You will play a key role in shaping our technology landscape and driving innovation. Job Responsibilities: * Engage with technical and business stakeholders to understand requirements and propose effective technical solutions. * Provide oversight and guidance to technology teams deploying workloads to public cloud environments. * Participate in architecture governance bodies to ensure alignment with organizational standards. * Execute creative solution design, development, and technical troubleshooting across software and infrastructure. * Drives adoption and governance of approved AI\-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI\-assisted code review/refactoring, test acceleration, release readiness, incident/root\-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain. * Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI\-assisted development and automation capabilities, to improve the value realized by automation at scale. * Identify gaps in current technologies and recommend improvements. * Lead evaluation sessions with external vendors, startups, and internal teams to assess architectural designs and technical credentials. * Identify opportunities to automate or eliminate recurring issues, improving operational stability. JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. J.P. Morgan's Commercial \& Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial \& Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world. Work Location: Karnataka, India Availability: Full time

Job Title: Lead Data Scientist Company: Philips Job Category: Machine Learning Roles & Responsibilities: Lead Data Scientist Job Description Job title: Lead Data Scientist Your Role The Lead Data Scientist architects, builds, and runs production\-grade Machine Learning and Generative AI systems—owning the full lifecycle from model development to scalable cloud deployment and ongoing performance monitoring . In addition, the role partners with commercial stakeholders translate market/customer data into decision\-ready insights and AI\-enabled analytics solutions that drive measurable outcomes Operating with a builder and translator mindset , the individual rapidly develops MVP analytics solutions , leverages AI to accelerate insight generation , and ensures strong product engineering fundamentals, data quality , and governance . The role plays a critical part in establishing a single source of truth for performance management across markets and channels while elevating analytics maturity from descriptive reporting to predictive and insight\-led decision making . Key Responsibilities * ML \& Deep Learning Model Development * Design, train, and optimize ML models for prediction, classification, ranking, time\-series forecasting, anomaly detection, NLP, and recommendation use cases. * Build robust experimentation workflows (train/validation strategy, ablations, error analysis) and improve model quality through iterative tuning. * Ensure reproducibility and maintainability through clean code practices, versioning, and automated testing. * GenAI Engineering (LLMs, RAG / MCP / fine\-tuning, Agents) * Build enterprise\-grade LLM applications using RAG (retrieval\-augmented generation), MCP, and fine\-tuning approaches: chunking strategies, embedding generation, hybrid retrieval, reranking, prompt templates, and citation/attribution patterns. * Develop LLM applications with tool use/function calling patterns and agentic workflows where appropriate. * Implement systematic evaluation: curated eval sets, prompt regression tests, hallucination checks, retrieval quality metrics, and automated quality gates. * ML \& LLM Operations: Productionization, Deployment \& Monitoring * Deploy and operate real\-time and batch inference solutions on Azure using managed endpoints and/or containerized serving. * Build CI/CD for ML systems: automated packaging, container builds, model validation tests, staged rollouts, and rollback strategies. * Establish lifecycle management: model registry/versioning, lineage, promotion workflows, and release governance. * Implement observability: latency, throughput, cost, drift signals, data quality checks, alerts, and performance degradation monitoring. * Pipeline Orchestration \& Automation (Train → Deploy) * Build standardized ML pipelines for training, evaluation, and deployment using orchestration tools (cloud\-native pipelines and/or platform tools). * Automate dataset/version management, feature generation, scheduled retraining triggers, and approval workflows. * Define repeatable patterns for scalable experimentation and reliable production delivery. * Analytics Products, Dashboards \& Data Governance * Own key analytics outputs as products (dashboards, reusable datasets, internal tools), continuously improving them based on usage patterns and performance gaps. * Build and automate dashboards and analytical components using scalable SQL logic, Python transformations, and reusable modules. * Act as owner for critical commercial/syndicated datasets (e.g., GfK, Circana, Nielsen or equivalent): definitions, assumptions, and limitations, ensuring transparent logic and trust in outputs. * Partner with data engineering/IT to ensure data quality, harmonization, and governance through strong validation and reconciliation practices. * Stakeholder Partnership \& Decision Support (Lightweight, High Impact) * Serve as trusted analytics thought partner to senior stakeholders (e.g., BU leadership, Sales, Marketing, Finance), shaping problem statements and aligning on success metrics. * Translate complex analytics into clear recommendations with a decision\-oriented storyline (“so\-what / now\-what”), tailored for leadership forums and reviews. * Support performance reviews, planning cycles, and high\-priority ad\-hoc requests with speed, rigor, and confidence; proactively challenge assumptions with fact\-based insights. * Responsible AI, Security, and Risk Controls (GenAI\-ready) * Implement guardrails: prompt injection defenses, sensitive data protections, output validation, and secure tool execution patterns. * Apply responsible AI practices: transparent evaluation criteria, auditability, and risk controls aligned to enterprise needs. * Technical Leadership (Lead\-level Expectations) * Set engineering standards for DS/ML codebases: design docs, code review practices, testing discipline, and production readiness checklists. * Mentor data scientists/ML engineers on modeling, GenAI engineering, and MLOps best practices. * Lead architectural decisions across modeling approaches, retrieval stack, serving patterns, and evaluation strategy. Core Skills \& Competencies Must\-have (Technical) * Strong Python (production\-quality coding) and solid CS fundamentals; strong SQL for data access and validation. * Depth in ML: Traditional ML exposure and at least one deep learning framework (PyTorch/TensorFlow), with strong understanding of metrics and failure modes. * GenAI implementation: RAG / MCP / fine\-tuning, embeddings/vector search, prompt orchestration, evaluation harnesses, and LLM application patterns. * Production deployment experience on AWS or Azure (model/LLM app deployment, API serving, scaling, monitoring). * MLOps tooling: experiment tracking, model registry, CI/CD, and pipeline orchestration (e.g., MLflow or equivalent patterns). Good\-to\-have (Business \+ Influence) * Strong business acumen and ability to connect disparate data points into compelling narratives that influence senior stakeholders. * Builder/MVP mindset—rapid prototyping and iterating based on stakeholder feedback while maintaining data quality and governance Note: This role values applied problem\-solving and business impact over purely academic specialization. You're The Right Fit If * Proven track record of owning end\-to\-end analytics domains, not just contributing to isolated analyses or consuming pre\-built reports. * 7–12\+ years in hands\-on Data Science / ML Engineering with multiple production deployments owned end\-to\-end. * Demonstrated ability to take solutions from experimentation → production (reproducible pipelines, deployment to managed endpoints/container platforms, monitoring \+ iterative improvement). * Strong GenAI delivery record: shipped RAG/MCP/fine\-tuned LLM applications with measurable quality controls, safety measures, and operational readiness. * Experience operating in complex, matrixed environments and partnering with senior stakeholders to drive insight\-led decision making * Hands\-on exposure to AI\-enabled analytics, including the use of GenAI tools (e.g., ChatGPT, Claude, or similar) to accelerate insight generation, analysis, or productivity. * Strong experience partnering with senior business stakeholders (BU leaders, Sales, Marketing, Finance), influencing decisions through insight\-led storytelling. Onsite roles require full\-time presence in the company’s facilities. Field roles are most effectively done outside of the company’s main facilities, generally at the customers’ or suppliers’ locations. this role is an office role. Work Location: Bengaluru, Karnataka, India Availability: Full time

Job Title: Lead Machine Learning Engineer Company: Bain & Company Job Category: Machine Learning Roles & Responsibilities: You’ll join our Machine Learning and Data Science experts within the \[2] Applied Tech \& AI team. This team is part of Bain’s digital capabilities practice, which includes experts in analytics, engineering, product management, and design. In this multidisciplinary environment, you'll leverage deep technical expertise with business acumen to help clients tackle their most transformative challenges. You’ll work on integrated teams alongside our general consultants and clients to develop data\-driven strategies and innovative solutions. Together, we create human\-centric solutions that harness the power of data and artificial intelligence to drive competitive advantage for our clients. Our collaborative and supportive work environment fosters creativity and continuous learning, enabling us to consistently deliver exceptional results. * Design, build, and deliver statistical/ML models and agentic AI/LLM solutions to solve high\-impact client problems. * Architect and implement production\-grade ML systems by building enterprise\-grade services, applying MLOps and CI/CD for reliable deployment and monitoring, and ensuring high standards in engineering quality and documentation. * Partner with general consulting teams and client stakeholders to translate business problems into ML solutions, prioritize work, and enable enterprise‑scale AI transformation. * Continuously research emerging frameworks and state‑of‑the‑art AI (e.g., LLMs, agents, retrieval, post\-training, etc.) and convert learnings into reusable frameworks, components, and accelerators used across industries and functions. * Share knowledge and mentor others on best practices tools, and approaches in applied machine learning and AI engineering. * Contribute to internal R\&D and learning initiatives to advance Bain’s AI capabilities and foster continuous innovation between projects. Work Location: Karnataka, India Availability: Full time