Job Title: Walk-in || Senior Associate (Front Office UI Automation Engineer) Company: Prohuman Technology Job Category: Machine Learning Roles & Responsibilities: Key Responsibilities * Design, develop and maintain UI automation scripts using Playwright with Python. * Build and enhance scalable, reusable automation frameworks. * Convert manual test cases into automated test scripts. * Develop and execute functional, regression and end\-to\-end test scenarios. * Implement BDD frameworks such as Behave or Cucumber. * Integrate automation suites into CI/CD pipelines using Jenkins. * Perform API testing and basic SQL\-based backend validation. * Manage test cases, execution and defect tracking using JIRA and XRay. * Perform debugging and root cause analysis of application issues. * Collaborate with QA, development and business teams throughout the SDLC. * Participate in Agile ceremonies, sprint planning and release activities. * Provide regular updates on test execution, defects and quality metrics. * Strong hands\-on experience with Playwright and Python. * Experience in UI automation framework development. * Strong Python scripting and programming skills. * Knowledge of BDD frameworks Behave / Cucumber. * Experience with Jenkins and CI/CD integration. * Knowledge of functional, regression and automation testing. * Experience with JIRA and XRay or similar test management tools. Work Location: Pune, Gurugram, Bengaluru, India Availability: Full time
Job Title: Senior Machine Learning Engineer Company: Docusign Job Category: Machine Learning Roles & Responsibilities: Company Overview Docusign brings agreements to life. More than 1\.8 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate the process of doing business and simplify people’s lives. With intelligent agreement management, Docusign unleashes business\-critical data that is trapped inside of documents. Until now, these were disconnected from business systems of record, costing businesses time, money, and opportunity. Using the Docusign AI\-native IAM platform, companies can create, commit, and manage agreements with solutions created by the \#1 company in e\-signature and contract lifecycle management (CLM). This position is an individual contributor role reporting to the Sr. Manager, Software Engineering. Responsibility * Design and implement the core knowledge graph and schema that model agreements, addenda, amendments, and related entities as explicit nodes and edges, enabling multi\-hop and hierarchical reasoning over complex contract portfolios * Build LLM Wiki style compilation pipelines that transform newly ingested agreements into structured, interconnected markdown or graph\-based knowledge bases, including concept, entity, and comparison pages that stay in sync with upstream document changes * Develop and productionize retrieval architectures that leverage the compiled knowledge base for high\-precision, multi\-step question answering and navigation across corporate hierarchies * Architect and implement Iris's long\-term memory (LTM) layer, including storage, retrieval, and summarization mechanisms that persist chat history, user actions in Canvas, and administrative overrides as episodic memories over time * Create ML and LLM components that fuse contract\-centric retrieval (GraphRAG \+ LLM Wiki) with institutional memory (LTM) so Iris can adapt behavior based on prior decisions, exemptions, and corrections without requiring users to restate context * Own the end\-to\-end lifecycle of these models and systems\-from feature and schema design through training, evaluation, deployment, and monitoring\-with a focus on reliability, safety, and debuggability in production environments Positions at Docusign are assigned a job designation of either In Office, Hybrid or Remote and are specific to the role/job. Preferred job designations are not guaranteed when changing positions within Docusign. Docusign reserves the right to change a position's job designation depending on business needs and as permitted by local law. We each have a responsibility to ensure every team member has an equal opportunity to succeed, to be heard, to exchange ideas openly, to build lasting relationships, and to do the work of their life. Best of all, you will be able to feel deep pride in the work you do, because your contribution helps us make the world better than we found it. And for that, you’ll be loved by us, our customers, and the world in which we live. Work Location: Bengaluru, Karnataka, India Availability: Full time
Job Title: Data Scientist Lead - Agentic Solutions Company: JPMorganChase Job Category: Machine Learning Roles & Responsibilities: JOB DESCRIPTION As the next push into this investment, JPMC is hiring the best talents to join our AI engineering team. We are executing like a startup and building the next generation technology that combines JPMC unique data and full\-service advantage to develop high impact AI applications and platforms in the financial services industry. We are looking for people who are excited about the opportunity. As a Data Scientist Lead at JPMorgan Chase, you design and deliver trusted market\-leading technology products in a secure, stable, and scalable way. Job Responsibilities * Designs and Implement LLM\-driven agent services for design, code generation, documentation, test creation and observability on AWS * Develops orchestration and communication layers between agents using frameworks like A2A SDK, LangGraph, or Auto Gen * Integrates AI agents with toolchains such as Jira, Bitbucket, Github, Terraform and monitoring platforms * Collaborates on system design, SDK development and data pipelines supporting agent intelligence * Provides technical leadership, mentorship, and guidance to junior engineers and team members. * 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. 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 Asset \& Wealth Management delivers industry\-leading investment management and private banking solutions. Asset Management provides individuals, advisors and institutions with strategies and expertise that span the full spectrum of asset classes through our global network of investment professionals. Wealth Management helps individuals, families and foundations take a more intentional approach to their wealth or finances to better define, focus and realize their goals. Work Location: Bengaluru, India Availability: Full time
Job Title: Senior Data Scientist Company: Epsilon Job Category: Machine Learning Roles & Responsibilities: The Automotive Practice at Epsilon is a rapidly growing team, driving growth for major players in the automotive industry \- from Original Equipment Manufacturers (OEMs) to dealerships across North America. Part of a 1,600\-member multinational team, the practice provides the automotive world’s largest service reminder platform, alongside agency services and digital media solutions. A leader in the automotive space, the team supports over 50% of auto dealerships in North America and maintains relationships with over 280 million customers. Home to innovation and ground breaking technology, our Auto team leads the game in developing outstanding software and solutions for hyper\-personalized digital marketing. The Automotive Data Science team within Epsilon partner with both internal and external clients and data providers, leverage predictive analytics and advanced modeling techniques to drive strategic thought and effective decision making. The core work charter includes supporting Retail and After Sales Service businesses for all the OEMs by developing solutions across the Customer Journey to drive Acquisition, Engagement, Retention using Advanced Analytics, Machine Learning, Deep Learning Capabilities and Data Platforms. About The Role The Sr. Data Scientist would support stakeholders by deploying projects from inception to insights and enable business strategy and impact for the clients. Contributes towards automation, process improvement and efficiency. Demonstrates innovative thinking, passion, and cross team collaboration. Establish strong working relationship with partners and coach junior data scientists in the team. Responsibilities * Deliver end to end Data Science projects including understanding of business requirements, exploratory data analysis, data processing, aggregating data, feature engineering, building, and validating predictive models, explaining model results and insights. * Use AI, ML, DL techniques such as regression, classification, clustering, tree\-based algorithms, support vector machine, and neural networks, recommender system, attribution modeling to address business problems. * Improve upon existing methodologies by developing new data sources/features, testing model enhancements, and fine\-tuning model parameters. * Provide requirements to develop analytical capabilities, platforms, and pipelines. * Present insights and recommendations to audiences of varying levels of technical sophistication * Automate processes to ensure scalability of solutions by collaborating with cross\-functional teams. * Coach junior data scientists and support delivering projects. Additional Information Epsilon is a global data, technology and services company that powers the marketing and advertising ecosystem. For decades, we’ve provided marketers from the world’s leading brands the data, technology and services they need to engage consumers with 1 View, 1 Vision and 1 Voice. 1 View of their universe of potential buyers. 1 Vision for engaging each individual. And 1 Voice to harmonize engagement across paid, owned and earned channels. Epsilon’s comprehensive portfolio of capabilities across our suite of digital media, messaging and loyalty solutions bridge the divide between marketing and advertising technology. We process 400\+ billion consumer actions each day using advanced AI and hold many patents of proprietary technology, including real\-time modeling languages and consumer privacy advancements. Thanks to the work of every employee, Epsilon has been consistently recognized as industry\-leading by Forrester, Adweek and the MRC. Epsilon is a global company with more than 9,000 employees around the world. * People centricity: We focus on employee well\-being in an environment where colleagues truly care about each other. * Collaboration: We work together, support one another, and collectively achieve goals. * Growth: There are endless opportunities for growth through learning, development and career advancement. * Innovation: We drive progress through cutting\-edge solutions and forward\-thinking approaches. * Flexibility: We’ve created a balance between work and personal life, and we encourage adaptability to solve problems creatively. Work Location: Bengaluru, Karnataka, India Availability: Full time
Job Title: Business Analyst Company: Thyrocare Job Category: Machine Learning Roles & Responsibilities: Responsibilities : Work Location: Navi Mumbai, Bengaluru, India Availability: Full time
Job Title: Artificial Intelligence Consultant Company: Artefact Job Category: Machine Learning Roles & Responsibilities: Role Overview We are seeking a Senior AI Engineer to join our growing AI and analytics team. The role involves building, deploying, and scaling AI solutions that support business transformation and data driven decision\-making across the organization. This position requires strong technical expertise, ownership mindset, and the ability to work collaboratively with cross\-functional teams. Key Responsibilities * Design, develop, and deploy end\-to\-end AI/ML solutions aligned with business objectives * Build and maintain robust machine learning pipelines, ensuring accuracy and scalability * Work with diverse datasets/sources/ERPs to develop generative, predictive, analytical, and automation\-driven models * Implement models using industry\-standard frameworks and best practices * Collaborate closely with product, engineering, and business stakeholders to translate requirements into technical solutions * Monitor, evaluate, and optimize model performance in production environments * Ensure compliance with data security, governance, and quality standards * Document solutions and contribute to technical knowledge repositories * Provide technical guidance and mentorship to junior team members Work Location: Bengaluru, Karnataka, India Availability: Full time
Job Title: Prompt Engineer Company: MEA Platforms Technologies Job Category: Machine Learning Roles & Responsibilities: We are looking for highly motivated Prompt Engineers to join our AI team and work on building and optimizing large\-scale document intelligence systems. This role involves designing, testing, and continuously improving prompts and AI workflows to extract, structure, and validate data from complex, unstructured documents. You will work closely with AI engineers, domain experts, and product teams to ensure high accuracy, consistency, and scalability of AI\-driven outputs. Key Responsibilities • Design, develop, and optimize prompts for LLM\-based workflows (extraction, QA, validation) • Support confidence calibration and validation logic • Familiarity with: Prompt chaining, Context management, Few\-shot / zero\-shot techniques Problem\-Solving \& Thinking Work Location: Bengaluru, India Availability: Full time
Job Title: Senior Machine Learning Engineer Company: Siemens Job Category: Machine Learning Roles & Responsibilities: We believe that a business can truly thrive only when its people are growing. That’s why we always put our people first. Our global and diverse team is here to support you—and challenge you—to grow in new ways. Who knows where our shared journey will take you? * Be the Architect \& Builder: Act as the technical engine for AI products. You are responsible for designing, developing, and implementing end\-to\-end AI products that solve high\-impact industrial challenges. * Revolutionize the Build: You don't just follow standard ML workflows; you innovate on how to build them faster. You will champion the use of Agentic Coding Frameworks and LLMOps to accelerate our time\-to\-market and automate the development lifecycle. * Iterate at Speed: Lead the technical execution of the product lifecycle using a lean, MVP\-driven approach. You focus on rapid prototyping, turning user feedback into code, and ensuring continuous deployment of production\-grade models. * Bridge Code \& Value: You speak "Deep Learning" and "Business Value" fluently. You will translate complex AI/Cloud architectures into scalable technical solutions, ensuring our technical debt stays low while our value delivery stays high. * Technical Leadership \& Mentorship: In a large organization, technical clarity is key. You will proactively clear technical roadblocks, mentor junior engineers, and align stakeholders on the feasibility and scalability of AI solutions. This role is based in Bangalore, offering the opportunity to work with teams that impact entire cities, countries—and the shape of things to come. Work Location: Bengaluru, India Availability: Full time
Job Title: I&P - GN - SONG - AI & Data - Platforms - AI/ML Engineering - Consultant Company: Accenture in India Job Category: Machine Learning Roles & Responsibilities: What You Will Do As an ML/AI Engineering Consultant, you will own the hands\-on design, development, testing, deployment, and monitoring of assigned machine learning and AI workstreams. You will combine model development with production engineering and lifecycle practices, while guiding junior team members and collaborating with cross\-functional client teams. * Translate defined business problems and user needs into data requirements, ML/AI problem statements, experiments, success metrics, detailed designs, and executable technical tasks. * Perform data exploration, feature engineering, model selection, training, tuning, evaluation, explainability, error analysis, and champion\-challenger comparisons. * Build predictive, forecasting, recommendation, optimization, NLP, computer vision, and other fit\-for\-purpose machine learning solutions. * Develop foundation\-model applications using prompt engineering, embeddings, vector search, Retrieval\-Augmented Generation, structured outputs, evaluation, and guardrails. * Implement agentic workflows using tool and function calling, planning, memory and context, orchestration, multi\-agent patterns, and human\-in\-the\-loop controls. * Engineer modular, production\-quality Python components, APIs and services, batch or real\-time inference workflows, containers, and enterprise integrations. * Implement AI lifecycle pipelines covering experiment tracking, data and model versioning, prompt or configuration versioning, registries, CI/CD, continuous training, promotion, rollback, and retraining. * Configure evaluation, monitoring, and observability for model quality, drift, robustness, safety, latency, reliability, cost, adoption, and business KPIs; troubleshoot production issues. * Apply Responsible AI, security, privacy, testing, reproducibility, auditability, and human oversight requirements throughout development and operations. * Collaborate with data engineers, software and cloud engineers, architects, UX teams, domain specialists, and product owners to deliver end\-to\-end solutions. * Own an assigned module or workstream, review code and model artefacts, coordinate Analysts or Senior Analysts, and manage day\-to\-day technical dependencies and risks. * Participate in client workshops, design walkthroughs, demonstrations, technical documentation, and contribution to reusable accelerators and practice assets. Work Location: Bengaluru, Karnataka, India Availability: Full time
Job Title: Associate, AI Data Scientist- Private Markets Company: BlackRock Job Category: Machine Learning Roles & Responsibilities: About This Role Build efficient, trusted agentic AI for private\-markets intelligence Research, build and scale advanced agentic systems and fit\-for\-purpose language models that turn complex information into dependable data, research and decision intelligence. Your team You will join a multidisciplinary AI and data science team focused on applying advanced AI to high\-value challenges in private markets. The team brings together data science, engineering, product and domain expertise, and works closely with users to develop practical capabilities that improve how information is acquired, researched and managed. Your role \& impact As an Associate, AI Data Scientist, you will be a hands\-on technical contributor responsible for researching, building and scaling enterprise\-grade agentic AI capabilities. Working directly with users and senior technical leaders, you will translate complex private\-markets workflows into well\-evaluated systems that move from experimentation to governed production and sustained adoption. Your core mandate is to advance multi\-agent LLM systems through effective agent design patterns, rigorous evaluation and disciplined model engineering. You will develop workflows that plan, retrieve, reason, use tools, verify and escalate appropriately, while selecting the simplest architecture and model that can meet the required quality, latency, cost and control objectives. You will also help establish the lifecycle for open\-source small language models and LLMs, from model discovery and benchmarking through training, adaptation, fine\-tuning, deployment, monitoring and retirement. Your impact will be visible in stronger data quality, faster research, scalable automation and reusable AI capabilities that help BlackRock Preqin remain at the forefront of private\-markets data and technology. Your responsibilities * Work forward\-deployed with researchers, data specialists and product teams to understand workflows, frame ambiguous problems, define measurable outcomes and iterate rapidly from evidence to production. * Research, design and deliver agentic workflows spanning planning, retrieval, tool use, structured extraction, reasoning, verification, exception handling and human escalation, using single\-agent or multi\-agent patterns where each is demonstrably appropriate. * Engineer advanced agent patterns, including bounded iterative loops, reflection and critique, planner\-executor and evaluator\-optimizer patterns, with explicit stop conditions, budgets and safeguards that prevent unproductive or uncontrolled execution. * Build agent and model harnesses that standardise tool interfaces, context assembly, state and memory handling, policy enforcement, tracing, replay and failure recovery. * Determine when an agentic architecture, retrieval workflow, specialised model or deterministic service is the best fit, and validate the decision against representative tasks and simpler baselines. * Design safe caching and reuse across retrieval, prompts, model responses, tool results and intermediate agent state, with clear cache keys, invalidation, freshness, access\-control and provenance requirements. * Build systematic evaluation harnesses using representative datasets, explicit quality dimensions, adversarial and edge\-case testing, regression suites, human feedback and monitored production outcomes. * Research and benchmark open\-source SLMs and LLMs for task fit, considering quality, inference performance, cost, licensing, security, deployment constraints and operational supportability; apply fit\-for\-purpose routing and batching where they improve efficiency. * Develop model\-adaptation strategies using prompt and context optimisation, supervised fine\-tuning, parameter\-efficient fine\-tuning or other suitable techniques, supported by governed dataset creation, experiment tracking, reproducibility and controlled promotion criteria. * Operate the lifecycle for trained and fine\-tuned open\-source models, including data and model versioning, lineage, experiment and artifact management, evaluation gates, registry and release controls, deployment, performance and drift monitoring, rollback, retraining triggers and retirement. * Build production\-quality Python components that integrate models with enterprise data, retrieval services, APIs, workflow orchestration and human\-review experiences. * Improve grounding and trust through attribution, provenance, uncertainty handling, validation checks, access controls and clear separation of source evidence from model\-generated conclusions. * Own delivered reliability across testing, observability, latency, cost and maintainability, and diagnose model, data, prompt and orchestration failures in production. * Document findings, reusable patterns and trade\-offs; contribute to design reviews; and communicate results clearly to research, product, engineering, risk and senior stakeholders. * Partner with engineering, product, risk, privacy, information security, legal and compliance colleagues to support responsible, secure and accountable use of AI. * Strong experience building and deploying AI or machine\-learning systems in an enterprise, SaaS, data\-product or similarly complex environment, with evidence of taking work beyond prototypes. * Practical depth in LLM applications and agentic systems, including retrieval, tool use, planning, orchestration, memory or state management, structured outputs, verification and evaluation of non\-deterministic behaviour. * Experience implementing and comparing bounded loops, reflection or critique, planner\-executor and evaluator\-optimizer patterns against simpler baselines, with measurable treatment of quality, reliability, latency, token usage, cost and failure modes. * Experience building agent or model harnesses across tool interfaces, context and state management, orchestration, policy enforcement, testing, tracing, replay, deployment and observability. * Hands\-on experience evaluating, selecting, training or adapting open\-source SLMs or LLMs, including benchmarking, governed dataset preparation, supervised or parameter\-efficient fine\-tuning and inference optimisation. * Practical ModelOps experience for trained or fine\-tuned models, including dataset and model lineage, experiment and artifact tracking, registries, evaluation gates, controlled release, performance and drift monitoring, rollback, retraining and retirement. * Experience designing model routing, batching and safe caching with appropriate keying, invalidation, freshness, privacy, access\-control and provenance safeguards. * Strong grounding in modern machine learning, experimentation and statistical evaluation, with disciplined handling of train\-test separation, leakage, uncertainty, reproducibility and model comparison. * Ability to write production\-quality Python and work effectively across data preparation, model development, APIs, orchestration, testing, deployment and observability. * Experience with unstructured or multimodal information, semantic retrieval, provenance and data\-quality engineering in workflows where domain experts provide ground truth and structured feedback. * Experience working directly with users or domain specialists to turn ambiguous needs into usable capabilities and iterate based on observed workflow outcomes. * Sound judgment on model and architecture trade\-offs across efficacy, efficiency, security, licensing, maintainability and operational risk. * Clear communication and collaborative delivery skills, with the ability to explain experiments, limitations and production trade\-offs to technical and non\-technical audiences. * Understanding of private markets, alternative investments, financial data or adjacent institutional\-investment workflows is desirable; curiosity and the ability to build domain depth quickly are essential. * Commitment to responsible AI, data provenance, privacy, security and meaningful human control in high\-trust enterprise workflows. Why this role This is an opportunity to work on consequential AI problems, real user workflows and high standards for trust. You will have meaningful hands\-on ownership, direct access to users and the opportunity to turn emerging agent and model techniques into durable capabilities with enterprise reach. Our hybrid work model BlackRock’s hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on increasing the impactful moments that arise when we work together in person – aligned with our commitment to performance and innovation. As a new joiner, you can count on this hybrid model to accelerate your learning and onboarding experience here at BlackRock. This mission would not be possible without our smartest investment – the one we make in our employees. It’s why we’re dedicated to creating an environment where our colleagues feel welcomed, valued and supported with networks, benefits and development opportunities to help them thrive. Work Location: Bengaluru, Karnataka, India Availability: Full time
