AI ML AND BUSINESS ANALYST in Pune, India - Jobeax
Vacancy description
AI ML AND BUSINESS ANALYST in Pune, India
awign expert
India, Pune
AI ML AND BUSINESS ANALYST in Pune, India is listed on Jobeax. Browse 30,000+ vacancies available.
Business Analyst Experience: 5–8 Years
Location: Pune (Preferred) | Urgency: Immediate
Shift: General OR 2-11 PM
Looking for Business Analysts with 5–8 years of experience in defining product requirements, managing AI/LLM-driven workflows, and collaborating with engineering teams. Should be able to translate business needs into clear technical specifications. Experience with Whiz AI or product-based environments is preferred. A strong product mindset is mandatory. Candidates who have worked for Saas and UI/UX products Business Analyst who has used AI/ML OR LLMs, OR agentic AI. Super good communication
... and cloud-based AI solutions. You will be responsible for designing, developing, and deploying intelligent solutions that leverage large language models (LLMs) and generative AI capabilities to solve complex business problems. Design and implement machine learning and generative AI models using Azure OpenAI and related services. ...
... in Generative AI (LLMs, embeddings, RAG, LLM‑based apps). - 6+ months of hands‑on experience with Agentic AI frameworks (CrewAI / AutoGen / LangGraph / LangChain Agents). - Strong proficiency in Python and ML libraries (Scikit‑learn, Pandas, NumPy). - Experience with OpenAI APIs, Azure OpenAI, HuggingFace, and prompt engineering. ...
... and responsible AI practices Collaborate with product, data, and platform teams to deliver business solutions Bachelor's or master's degree in computer science, AI, Data Science, or related field Experience 3–5 years of experience in software/ML engineering At least 1–2 years of hands-on experience in Generative AI / LLM-based ...
... and generation of synthetic data. This involves cleaning, labeling, and augmenting data to train and improve AI models. Experience in developing and deploying AI models in production environments. Knowledge of cloud services (AWS, Azure, GCP) and understanding of containerization technologies like Docker and orchestration ...
... Platform Development Drive the architecture of AI-native commercial data platform, ensuring it is modular, scalable, and agent-ready. Collaborate with product and data teams to translate pharma commercial business requirements into agentic workflows. Ensure data governance, compliance (HIPAA, GDPR), and security standards ...
... Generative AI, GPT/LLMs and Agentic AI across business applications. Key Responsibilities Reuse and enhance existing AI/Generative AI libraries, platforms, models and assets . Research and develop novel AI and Generative AI algorithms and techniques . Design, develop and optimize end-to-end AI/ML solutions for various applications. ...
... throughput, and cost efficiency in cloud environments. Integrate GenAI APIs (OpenAI, Anthropic, Google Cloud GenAI, Azure OpenAI) into enterprise applications and co-pilot solutions. Establish MLOps best practices for observability, reproducibility, and secure deployment of GenAI workloads. Stay updated on GenAI research ...
... applications.- Design and optimize RAG pipelines, AI Agents, and multi-agent workflows.- Lead ML pipeline deployment, monitoring, and optimization.- Develop FastAPI-based AI services.- Implement semantic search using Vector Databases.- Mentor junior engineers and conduct code reviews.- Collaborate with business stakeholders and global ...
... risk management, quality, and timelines.- Translate business requirements into clear technical designs and execution plans.- Review architecture, code quality, and engineering best practices; ensure scalable and maintainable solutions.- Drive adoption of AI capabilities (e.g., ML models, GenAI, intelligent automation) in ...
... reliability, performance, and cost efficiency. This role will work closely with business stakeholders, product teams, and engineering squads to translate complex business requirements into robust technical solutions that enable advanced analytics, AI/ML, and data-driven decision-making across insurance focused business domains. ...
... Strong experience in ML/DL model development , including training, fine-tuning, and evaluation. - Proven experience in team monitoring, performance tracking, and delivery management . - Demonstrated ability in mentoring, coaching, and leading engineering teams . - RIA Advisory LLC (RIA) is a business advisory and technology ...
... compliance, documentation, and stakeholder communication. Candidate Persona - 8-12 years of Project Management experience in technology companies . - Proven experience handling enterprise-level Indian customers , understanding their business culture and delivery expectations. - Strong exposure to AI/ML-based product implementations ...
... Define enterprise AI reference architecture and roadmap.- Mentor engineers and ML teams on best practices for agentic AI design.- Lead build vs buy decisions for AI platforms and tools.- Establish AI cost governance and FinOps framework.- Drive cross-functional alignment between business, data, and engineering https://jobeax.com/link/7CpQ1UBuqJUS25b5 ...
... Deloitte Technology Fast 500™ ranked AiDASH No. AiDash is looking for an experienced Manager – AI Data Ops to lead a team responsible for sourcing, processing, and annotating satellite and remote sensing imagery that powers our AI/ML models. This role blends hands-on GIS expertise with strong people management and vendor ...
... Design distributed, cloud-native, API-driven, and data-intensive applications on Azure and/or AWS.- Implement scalable solutions using Docker, Kubernetes, CI/CD, and infrastructure-as-code practices.- Collaborate with architecture, cloud, security, operations, product, and business teams to deliver reliable and secure AI https://jobeax.com/link/iKfkA8JidHXTKcLW ...
... Gurgaon to drive AI-driven healthcare innovations. The ideal candidate has 3+ years of AI/ML experience, 1+ year of GenAI production experience, and 1+ year of hands-on GenAI product development. You need to have a strong data science background and have expertise in GenAI, Agentic AI deployments, causal inference, and Bayesian ...
... platforms. Exposure to annotation/ML workflow tools or ML model validation platforms. Comfort working in Agile, distributed teams using tools like Git, JIRA, and Slack. You'll work at the intersection of AI, data infrastructure, and impact—contributing to platforms that ensure AI is explainable, auditable, and ethical ...
... Design distributed, cloud-native, API-driven, and data-intensive applications on Azure and/or AWS.- Implement scalable solutions using Docker, Kubernetes, CI/CD, and infrastructure-as-code practices.- Collaborate with architecture, cloud, security, operations, product, and business teams to deliver reliable and secure AI https://jobeax.com/link/iKfkA8JidHXTKcLW ...
... development, and production deployment . You will work closely with engineering, product, and business teams to translate requirements into scalable AI/ML solutions and take models from experimentation through production. Requirements KEY RESPONSIBILITIES - Design, develop, test, and deploy scalable AI/ML models and solutions ...