AI / ML Engineer
- Compensation
- Not disclosed
- Location
- Mumbai (All Areas)
- Work setup
- Onsite
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Ml / AI
- Posted
Skills
Nice to have
- Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence,
- or a related technical field.
- Experience fine-tuning open-source LLMs or implementing advanced RAG
- optimizations.
- Certifications from AWS, Azure, or GCP in Machine Learning or Cloud Architecture.
Full description
Job Description
Job Title: AI Engineer / Data Scientist (35 YoE)
Location: Mumbai, Kandivali
Experience: 35 Years
About the Role
We are looking for an energetic, hands-on AI Engineer / Data Scientist with 3 to 5 years of
experience to join our core AI and engineering team. In this role, you will design, build, and
scale production-grade machine learning and Generative AI systems.
You will work at the intersection of data science and software engineering, taking models from
conception and functional development to scalable cloud deployment on AWS/Azure/GCP. If
you are passionate about building high-performance AI solutions, working with LLMs/GenAI
tools, and writing clean, production-ready Python code, we want to hear from you.
Key ResponsibilitiesGenAI & AI Solution Development: Design and deploy modern Generative AI
solutions, including Large Language Model (LLM) integrations, Retrieval-Augmented
Generation (RAG) pipelines, prompt engineering, and agentic workflows.
Production Systems & MLOps: Build, containerize, and deploy scalable machine
learning inference pipelines and APIs into production environments. Monitor, optimize,
and troubleshoot model performance, latency, and costs in cloud environments.
Model Development & Experimentation: Apply a strong functional understanding of
machine learning and deep learning algorithms. Perform exploratory data analysis,
feature engineering, fine-tuning, and rigorous model evaluation.
Cloud Infrastructure (CSP): Leverage cloud services (AWS, Azure, or GCP) to
architect robust data and AI workflows, utilizing managed AI services, container
registries, and serverless/compute instances.
Cross-Functional Collaboration: Partner closely with software engineering, product,
and data teams to seamlessly integrate AI capabilities into customer-facing applications.Required Qualifications & SkillsExperience: 3–5 years of professional experience in data science, machine learning, or
AI engineering, with a proven track record of shipping systems to production.