Associate AI/ML Engineer
UnitedHealth Group
Bengaluru, Karnataka, IndiaENTRY
AIMLEngineer
Job Description
Seeking an Associate AI/ML Engineer with strong foundational skills.
Responsibilities
- AI/ML Solution Development
- Design, implement, and optimize AI and machine learning solutions, including statistical models, deep learning, and Generative AI systems
- Model Training, Evaluation & Optimization
- Execute proof‑of‑concepts, train models at scale, and baseline performance using quantitative evaluation metrics
- Platform & Infrastructure Engineering
- Build and operate large‑scale training and inference pipelines using Databricks, PySpark, and cloud platforms (AWS, Azure, GCP)
- Generative AI & Advanced Techniques
- Apply RAG, LangChain, and Vector Databases to develop GenAI solutions
- Optimize and quantize models to improve performance, scalability, and cost efficiency
- Software Engineering & APIs
- Develop REST and FastAPI services, containerize solutions using Docker, and integrate UI tools such as Streamlit or Flask
- Collaboration & Communication
- Partner with cross‑functional teams to translate business needs into clear, scalable AI solutions, and present insights effectively
- Leadership, Mentorship & Culture
- Mentor engineers, participate in design and architecture reviews, and uphold standards for quality, safety, and trust
Qualifications
- Bachelor's or Master's degree in Computer Science, Data Science, or a related field
- Software & AI/ML Engineering Experience
- 1+ years of professional software engineering experience, delivering high‑quality, production‑grade commercial applications end to end
- 1+ years of AI/ML engineering experience, including deploying models at scale and contributing to technical leadership across AI initiatives
- Demonstrated ability to design, build, deploy, and operate production‑ready services, including CI/CD and cloud infrastructure
- Programming & Systems Expertise
- 1+ years of hands‑on experience with Java, Python, SQL, and scripting
- Proven solid foundation in clean, maintainable code, system design, API development, and modern software engineering best practices
- Cloud & Data Platform Experience
- 1+ years of experience across AWS, Azure, and GCP, with deeper hands‑on experience in AWS and cloud‑native architectures
- Knowledge with Databricks, MongoDB, PySpark/SparkSQL, and data pipeline implementation
- Familiarity with Hadoop ecosystems and distributed data processing
- MLOps, Infrastructure & Governance
- Working knowledge of MLOps practices, including model lifecycle management and operationalization
- Familiarity with Infrastructure as Code using Terraform and CloudFormation
- Technical Expertise
- Solid knowledge of AI/ML frameworks, orchestration tools, and scalable architectures
- Proficiency with big data technologies, including Spark, Hadoop, and Kafka
- Solid foundation in data science principles, including statistics, probability theory, optimization, simulation, and data modeling
- Solid alignment is with software engineering fundamentals, including system design, clean and maintainable coding, and building production‑ready services end to end, from development through deployment and cloud infrastructure
- Comfortable working across AWS and cloud‑native architectures, with increasing hands‑on application of AI concepts, particularly LLMs and RAG‑based solutions
- Completed AI Dojo Generative AI training, strengthening applied Generative AI foundations and practical implementation skills
- Actively developing deeper expertise in core machine learning and data engineering, including:
- Traditional ML models, algorithms, and evaluation techniques
- Feature engineering and data pipelines
- Large‑scale data processing using Spark and Databricks
- Highly motivated to close skill gaps through structured training, mentorship, and hands‑on learning, and values collaboration and knowledge‑sharing within the team
Nice to have
- Hands-on experience with cloud platforms
- Understanding of data governance