Job Title: Data Scientist Company: SourcingXPress Job Category: Machine Learning Roles & Responsibilities: Job Description Core Responsibilities * Data Preparation: Collect, clean, validate, and preprocess structured and unstructured data. * Model Development: Build machine learning algorithms, predictive models, and statistical experiments. * Deployment \& Testing: Implement models into production systems and monitor performance. * Collaboration \& Communication: Work with product managers, software engineers, and data engineers, while presenting findings via data visualizations. \[1, 2, 3, 4, 5] Work Location: Bengaluru, Karnataka, India Availability: Full time

Job Title: Staff Machine Learning Engineer Company: Warner Bros. Discovery Job Category: Machine Learning Roles & Responsibilities: Roles \& Responsibilities * Own the architecture and roadmap of the model serving runtime, supporting multiple ML frameworks and inference engines behind one control plane * Lead large\-scale migrations and rollouts of production models onto the platform with zero viewer\-facing regressions * Build and maintain serving backends, model configurations and batching strategies that meet strict tail\-latency targets at high request volume * Design autoscaling, capacity management and multi\-region resilience for latency\[1]critical serving across Max, Discovery\+ and other WBD offerings * Drive observability, cost optimization and performance tuning across the serving fleet, including hardware selection, GPU and CPU utilization, and model optimization * Define the contract between model training and serving so a validated model artifact deploys to production through standard, automated paths * Establish per\-model SLOs with model owners and build the telemetry that proves them * Collaborate with applied scientists, partner engineering teams and the core infrastructure team as the platform onboards new models, runtimes and markets * Author, test, review and optimize production\-level code in Python while executing best practices in version control, CI/CD and code integration * Take part in the platform on\-call rotation and lead incident reviews that result in design changes, not just fixes * Contribute design documents and technical documentation to support architecture decisions, knowledge transfer and sharing * Mentor engineers, raise the bar in design and code reviews, and represent the platform in cross\-team architecture decisions * 9\+ years of industry experience * 5\+ years of experience building or operating production ML infrastructure or comparable low\-latency, large\-scale distributed systems with a large customer base * Hands\-on experience running model inference in production at scale * Strong Kubernetes fundamentals and experience running GPU and CPU workloads on it * Proven performance engineering skills: profiling, tail\-latency analysis, batching and concurrency under load * 7\+ years of programming experience in Python, plus working fluency in a systems language such as C\+\+, Go or Rust * Good practical knowledge of the modern machine learning lifecycle, from training artifacts through deployment, rollout and monitoring * Strong architectural and design skills, with a track record of leading multi\-quarter technical initiatives across teams * Operational maturity: experience owning a tier\-1 service, including on\-call * Experience with one of the cloud platforms AWS/GCP/Azure, Docker and Kubernetes, and CI/CD tools like GitHub Actions, Jenkins etc. * Excellent written and verbal communication skills; comfortable contributing to technical documentation and on\-call support * Ability to technically collaborate with partners across time zones We embrace the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit. In line with the laws of the country or region in which the role is based, this includes consideration without regard to race, color, ethnicity, national origin, citizenship status, religion or belief, sex, gender, gender identity or expression, sexual orientation, age, marital status, pregnancy, parenthood, physical or mental disability, genetic information, military or protected veteran status, union status or any other category protected by applicable law. Work Location: Bengaluru, India Availability: Full time

Job Title: Software Engineer, GenAI Engineering (AI/ML) Company: Pegasystems Job Category: Machine Learning Roles & Responsibilities: Pega is changing the way the world builds software. Our goal is to be the no. 1 CRM SaaS company in the world. In this role, you will design, build and deploy the GenAI services and AI agents behind Pega Infinity and the Pega AI Assistant. That includes agent tools and MCP integrations, retrieval\-augmented generation (RAG) and knowledge services, AI guardrails and governance, and agent observability. You'll lead features end to end, from problem framing to production, on cloud\-native services that run securely at enterprise scale on AWS, GCP and customer\-hosted environments. At Pega, we actively explore and embrace emerging AI capabilities with curiosity, responsibility, and a drive for meaningful innovation. You will work in an environment where AI enabled tools are used to enhance learning, improve engineering efficiency, and support better decision making across the cloud platform. We expect engineers to apply critical thinking to all AI generated outputs—validating accuracy, quality, and relevance before applying them in production environments. We view AI maturity as a spectrum, progressing from foundational adoption toward more strategic, advocacy driven integration, and you will play an active role in that journey. * Develop AI\-based applications and algorithms. * Design, test, and build software components for AI applications. * Collaborate with data scientists on algorithm development. * Create prototypes and proofs\-of\-concept for new ideas. * Create state\-of\-the\-art harness that powers Pega Agents * Lead model development, implementation and deployment end\-to\-end including. ML operations. You will be driving problem formulation, modeling approach, implementation, testing, deployment and monitoring. * Partner with product managers to drive productization of ideas into shippable solutions * Communicate effectively with technical and non\-technical audiences Who You Are: ---------------- * Gartner Analyst acclaimed technology leadership across our categories of products. * Continuous learning and development opportunities * An innovative, inclusive, agile, flexible, and fun work environment. * Competitive global benefits program inclusive of pay \+ bonus incentive, employee equity in the company. Pega embraces the responsible use of artificial intelligence (AI) to improve efficiency, consistency, and fairness across our business. We encourage thoughtful and ethical adoption of AI technologies that support people—not replace them. We may use AI‑enabled tools in our recruitment process. These tools are designed to assist us by providing insights and operational support. Work Location: Bengaluru, India Availability: Full time

Job Title: Distinguished AI Engineer Company: Capital One Job Category: Machine Learning Roles & Responsibilities: In this role, you will: * Partner with a cross\-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI\-powered products that change how our associates work and how our customers interact with Capital One. * Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, evals engine, experimentation, governance, and observability, etc. * Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. * Invent and introduce state\-of\-the\-art LLM optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. * Devise novel context generation techniques that optimize cost / quality trade\-offs. * Design and implement capabilities for automated monitoring, anomaly detection and RCA for multi\-turn and headless agentic applications. * You will collaborate with lines of businesses to design and implement high value agentic applications * Finally you will coach and evangelize, mentoring Staff, Principal and Senior engineers, authoring technical design documents and blogs and representing Capital One at Tier1 AI conferences. Preferred Qualifications: * 10\+ years of experience deploying scalable and responsible solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) * 4\+ years of experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems * 6\+ years of experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C\+\+, C\#, Java, or Golang * 2\+ years of experience with Agentic frameworks (LangChain, CrewAI, AutoGen etc.) * 2\+ years of experience leading GenAI or LLM\-Powered application architectures in production * 2\+ years of experience developing and applying state\-of\-the\-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost * 2\+ years of experience with Observability and Evals for agentic applications * Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production * Demonstrated ability to lead and mentor multiple engineering teams and influence cross\-functional stakeholders up to the VP level * Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers * Master’s or Ph.D in Computer Science, Computer Engineering, especially in AI/ML areas. For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com Work Location: Bengaluru, Karnataka, India Availability: Full time

Job Title: Applied AI Engineer Sales Force - Software Engineer II Company: Deloitte Job Category: Machine Learning Roles & Responsibilities: Summary Position Summary Applied AI Engineer I Role Overview: As a Salesforce Applied AI Engineer I , you will actively engage in your engineering craft, taking a hands\-on approach to building and enhancing high\-visibility, full\-stack products that serve the business and its users. Your expertise will be pivotal in delighting customers and users, while driving tangible value across Deloitte’s product and AI investments. You will leverage your extensive engineering craftsmanship across full\-stack software engineering and modern frameworks—together with applied AI fluency that lets you build GenAI and agentic capabilities directly into the products you deliver—consistently demonstrating your strong track record in delivering high\-quality, outcome\-focused solutions. The ideal candidate will be a dependable team player, collaborating with cross\-functional teams to design, build, and ship products end to end, from concept through production. Key Responsibilities: * Embrace and drive a culture of accountability for customer and business outcomes—and for the cost of achieving them. Develop engineering solutions that solve complex problems with valuable outcomes, ensuring high\-quality, lean designs and implementations, and owning the inference, token, and cloud cost of what you build. * Serve as the technical advocate for products, ensuring code integrity, feasibility, and alignment with business and customer goals. Lead requirement analysis, component design, development, testing, integrations, and support. * Maintain accountability for code\-design integrity, implementation fidelity to architecture and tech stack, quality, data, and ongoing maintenance and operations. Be hands\-on, self\-driven, and continuously learn new approaches, languages, and frameworks. Create technical specifications, and write high\-quality, supportable, scalable code ensuring all quality KPIs are met or exceeded. Demonstrate collaborative skills to work effectively with diverse teams. * Develop lean engineering solutions through rapid, inexpensive experimentation to solve customer needs. Engage with customers and product teams before, during, and after delivery to ensure the right solution is delivered at the right time. * Adopt a mindset that favors action and evidence over extensive planning. Utilize a leaning\-forward approach to navigate complexity and uncertainty, delivering lean, supportable, and maintainable solutions. * Work collaboratively with empowered, cross\-functional teams including product management, experience, and delivery. Integrate diverse perspectives to make well\-informed decisions that balance feasibility, viability, usability, and value. Foster a collaborative environment that enhances team synergy and innovation. * Possess expertise in modern software engineering practices and principles, including AI and Agentic SSDLC to deliver daily product deployments using full automation from discovery to production to operations with all quality checks through SSDLC lifecycle. Strive to be a role model, leveraging these techniques to optimize solutioning and product delivery. Demonstrate strong understanding of the full lifecycle product development, focusing on continuous improvement and learning. * Quickly acquire domain\-specific knowledge relevant to the business or product. Translate business/user needs, architectures, and UX/UI designs into technical specifications and code. 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. 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 . Work Location: Bengaluru, Karnataka, India Availability: Full time

Job Title: Senior Machine Learning Engineer Company: Quantiphi Job Category: Machine Learning Roles & Responsibilities: Good To Have Skills * Hands\-on experience with OCR/Document Intelligence engines and NLP techniques for extracting structured information from documents and images. * Hands\-on experience with Bedrock Agentcore * Hands\-on experience with OpenAI, Anthropic, Gemini, or other foundation models. * Experience with Docker, Kubernetes, and MLOps practices. * Experience with Redshift, SQL, DynamoDB, or AWS Glue. * Exposure to model monitoring, evaluation, and observability for GenAI applications. * Ability to work in an Agile and DevOps environment. Work Location: Bengaluru, Karnataka, India Availability: Full time

Job Title: Risk Analyst Company: EY Job Category: Machine Learning Roles & Responsibilities: Within Information Security we blend risk strategy, digital identity, cyber defense, application security and technology solutions as we consider the entire security lifecycle. You will join a team of hardworking, security\-focused individuals dedicated to supporting, protecting, and enabling the business through innovative, secure solutions that provide speed to market and business value. The Technology Assurance, Risk, and Policy (TARP) function within Information Security strives to create and promote a holistic Governance, Risk, and Compliance (GRC) program by creating a robust, resilient, and proactive governance framework, supported by a strategic risk management approach and stringent compliance structures. It aims to integrate and align its GRC initiatives in line with the global firm’s objectives and emerging threats within the cybersecurity landscape. Furthermore, the Policy, Risk, and Controls (PRC) Enablement \& Awareness team aims to manage the human element of risk through Human Risk Management, which involves security awareness, training, culture, and behavior management. Your key responsibilities The Global Behavioral Analytics \& AI Specialist sits within the Human Risk Management function and leverages artificial intelligence, data science, and behavioral science to measure, model, and manage human risk across EY. This role is the analytical and AI engine behind the security culture program—turning behavioral signals, engagement data, and risk indicators into insight that helps the organization understand why people behave the way they do and how to manage those behaviors at scale. Reporting to the Global Security Culture and Engagement Lead, this individual will partner across the awareness, learning, training, and simulation teams to build the metrics, models, and AI\-enabled capabilities that quantify culture and behavior change. Beyond measurement, they will act as an AI\-forward thought partner for the entire Human Risk Management team—identifying practical, responsible ways to apply AI both for intelligence and for service delivery. Key responsibilities include * Maintain and optimize a human risk measurement framework, defining the metrics and indicators that quantify security behaviors, culture, engagement, and human risk across the organization. * Leverage AI to analyze behavioral data, identify patterns and human risk indicators, and model or predict where risky behaviors are most likely to occur. * Work with stakeholders to consolidate data from across the Human Risk Management program into reporting that tells a clear, connected story. * Serve as the AI\-forward thought partner for the Human Risk Management team, identifying responsible and practical ways to apply AI for both intelligence (measurement, prediction, insight) and service offerings (e.g., AI\-powered solutions that reinforce secure behaviors). * Partner with the Security Culture and Engagement Lead to translate behavioral insight into targeted interventions, campaigns, and reinforcement strategies. * Develop executive\-ready reporting, visualizations, and recommendations that communicate human risk trends, program effectiveness, and return on investment to senior stakeholders. * Design and analyze surveys, assessments, experiments, and A/B tests to evaluate the impact of behavior change initiatives and continuously improve them. * Ensure that data and AI are used responsibly, ethically, and in line with EY privacy, data protection, security, and governance requirements. * Stay informed on developments in behavioral science, data science, AI, and human risk measurement, bringing new methods and innovation into the program. We’re looking for someone who can collaborate globally with different regions and cultures. Problem\-solves, thinks creatively, and has an open mind to new insights. Focus on customer service and building positive relationships with colleagues both across teams and globally. A highly motivated, diligent, and driven individual who seeks development and improvement opportunities and deliver quality services. As part of this role, you will work in a highly coordinated, globally diverse team with the opportunity and tools to grow, develop and drive your career forward. Here, you can combine global opportunity with flexible working. The EY benefits package goes above and beyond too, focusing on your physical, emotional, financial, and social well\-being. Your recruiter can talk to you about the benefits available in your country. Here’s a snapshot of what we offer: * Continuous learning: You will develop the mindset and skills to navigate whatever comes next. * Success as defined by you: We will provide the tools and flexibility, so you can make a significant impact, your way. * Transformative leadership: We will give you the insights, coaching and confidence to be the leader the world needs. * Diverse and inclusive culture: You will be accepted for who you are and empowered to use your voice to help others find theirs. Work Location: Bengaluru, India Availability: Full time

Job Title: AI and ML Engineer Company: Sandisk Job Category: Machine Learning Roles & Responsibilities: Sandisk meets people and businesses at the intersection of their aspirations and the moment, enabling them to keep moving and pushing possibility forward. We do this through the balance of our powerhouse manufacturing capabilities and our industry\-leading portfolio of products that are recognized globally for innovation, performance and quality. Description We are seeking a talented AI/ML Engineer in Data and AI team to drive the design, development, and operationalization of machine learning and GenAI solutions across Sandisk's enterprise. In this role, you will own end\-to\-end AI/ML projects, from problem framing and data strategy through model deployment and monitoring. You will partner directly with business stakeholders to translate complex requirements into scalable, production\-grade solutions and mentor junior engineers on the team. Key Responsibilities * Design, develop, and implement machine learning models and statistical analyses to address manufacturing, supply chain, and product quality challenges. * Conduct exploratory data analysis and present actionable insights and recommendations to stakeholders. * Develop prompt engineering strategies and feedback loops for LLM optimization; capture and normalize LLM interactions into reusable Knowledge Artifacts. * Implement Retrieval\-Augmented Generation (RAG) pipelines, including document parsing, chunking, vectorization, and semantic search using embeddings and vector databases. Support domain\-specific ontologies, taxonomies, governance and versioning. * Support agentic workflows using industry\-standard frameworks for autonomous task orchestration and multi\-step reasoning, with safe and controlled execution via constraints, policies, and fallback paths. * Contribute to establishing and maintaining data quality standards, implementing validation frameworks and monitoring systems. * Support the deployment and monitoring of machine learning models in production environments, including performance tracking and drift detection. * Stay current with emerging data science technologies, methodologies, and industry trends, evaluating their applicability to organizational needs. * Support end\-to\-end project delivery, ensuring timely completion and alignment with business objectives. * Experience with Large Language Models (LLMs), prompt engineering, and GenAI application development. * Familiarity with vector databases, embedding models, and semantic search architectures. * Experience building agentic AI workflows and multi\-LLM orchestration systems. * Hands\-on experience with data visualization and business intelligence tools such as Tableau, Power BI, or equivalent platforms. * Experience using version control systems (Git) and collaborative software development practices. * Experience deploying, monitoring, or maintaining machine learning models in production environments. * Familiarity with cloud platforms (Azure, AWS, or GCP) and Lakehouse architectures (e.g., Databricks). Work Location: Bengaluru, Karnataka, India Availability: Full time

Job Title: Software Development Trainee-2 Company: WEX Inc. Job Category: Machine Learning Roles & Responsibilities: WEX is a global commerce platform that has been simplifying the way businesses operate for over 40 years. Our purpose is simple: to reduce administrative burdens, streamline payments, and manage mobility. With a team of over 7,200 professionals across 16 countries. You won't just be a bystander; you'll work on impactful projects and contribute to WEX’s mission. We provide mentorship, professional development, and weekly learning experiences to help you build confidence and leadership skills. High\-performing interns may even get the chance to lead their own initiatives. We offer remote, hybrid, and onsite options for flexibility, and our goal is to bring top interns back full\-time or offer them extended roles during the school year. About the Team/Role: Work Location: Bengaluru, India Availability: Full time

Job Title: Lead Data Scientist Company: Ecolab Job Category: Machine Learning Roles & Responsibilities: Role Summary As a Lead Data Scientist, you will lead the design, development, validation, and operationalization of machine learning and advanced analytics solutions that power intelligent products and business capabilities. This role combines strong hands\-on expertise in model development with practical experience in MLOps, deployment, monitoring, and lifecycle management. You will work closely with product managers, domain experts, engineers, architects, and platform teams to turn business problems into scalable, production\-grade ML solutions. In addition to building models, you will guide feature engineering strategies, experimentation approaches, validation standards, and production\-readiness practices to ensure models are reliable, explainable, and maintainable in real\-world environments. This role is ideal for someone who is equally comfortable developing models, operationalizing them in production, and mentoring others to raise the maturity of data science and ML engineering practices across the team.. Key Responsibilities * Lead the design, development, evaluation, and deployment of machine learning models for predictive, classification, recommendation, anomaly detection, forecasting, and optimization use cases * Translate business and product requirements into well\-defined analytical approaches, model strategies, feature sets, evaluation methods, and deployment plans * Build robust and reusable pipelines for data preparation, feature engineering, model training, validation, hyperparameter tuning, and model packaging * Develop and operationalize production\-grade ML solutions with strong focus on reproducibility, maintainability, scalability, and measurable business impact * Partner with data engineers and software engineers to integrate models into applications, APIs, workflows, and downstream business systems * Design and implement MLOps practices including experiment tracking, model versioning, automated deployment, CI/CD for ML, monitoring, drift detection, retraining strategies, and rollback readiness * Establish model performance baselines and monitor production behavior for accuracy, drift, latency, stability, explainability, and business outcomes * Contribute to best practices for model governance, feature lineage, documentation, testing, interpretability, and responsible AI * Guide technical decisions on ML solution design, operationalization patterns, and production support expectations * Mentor other data scientists and ML engineers on modeling rigor, experimentation practices, and production\-readiness standards * Contribute reusable assets such as feature templates, modeling utilities, evaluation frameworks, deployment patterns, and internal accelerators * Work with tools and platforms such as Azure Machine Learning, Databricks, MLflow, Azure DevOps, GitHub, Docker, Kubernetes, Azure Functions, Azure Container Apps, Azure Monitor, and Application Insights (or equivalent platforms and tools) Preferred Qualifications * Experience leading complex ML initiatives involving multiple models, cross\-functional teams, and production operationalization * Experience with time\-series forecasting, optimization, recommender systems, anomaly detection, NLP, or domain\-specific applied AI use cases * Familiarity with LLM\-assisted analytics, embeddings, retrieval\-enhanced ML workflows, or hybrid ML \+ GenAI solution patterns * Experience integrating ML solutions into enterprise applications, APIs, business workflows, and digital products * Experience with feature stores, explainability frameworks, responsible AI toolkits, and model governance controls * Familiarity with Azure OpenAI, Azure AI Studio, Azure AI Search, or equivalent platforms where ML and GenAI capabilities coexist * Experience contributing reusable frameworks, MLOps standards, internal accelerators, or shared data science utilities * Working knowledge of distributed training, large\-scale data processing, and performance optimization in production environments * Experience with advanced MLOps and platform tooling such as MLflow, Kubeflow, Azure ML, TensorBoard/ TensorFlow Extended, or equivalent ecosystem tools * Experience operating in a build\-own\-operate product environment with strong expectations around reliability, observability, supportability, and continuous improvement * Ability to influence architectural and platform decisions for ML\-enabled products while remaining hands\-on in model development and operationalization Work Location: Bengaluru East, Karnataka, India Availability: Full time