AI/ML Engineer
Position:
AI/ML EngineerJob Description:
Role: AI/ML Engineer
Location: Ahmedabad, Pune, Indore
Years of Experience: 4 to 8 years
Notice Period – 0-45 Days (Preferred)
Must-Have (Mandatory)
- Machine Learning: Deep understanding of supervised, unsupervised, and reinforcement learning, model evaluation, and feature engineering.
- Deep Learning: Proficiency with TensorFlow, PyTorch, Keras; hands-on with CNNs, RNNs.
- Programming: Expert in Python (NumPy, Pandas, scikit-learn, etc.); R exposure acceptable.
- Big Data Technologies: Practical experience with Spark (Databricks preferred); familiarity with Hadoop/Kafka.
- Cloud Platforms: Azure or AWS or GCP (ML services, data storage, compute), with strong MLOps exposure.
- Data Warehousing & Databases: Strong SQL, NoSQL, and data modeling.
- Drift Detection & Monitoring: Hands-on experience with model drift detection, monitoring, and automated alerts.
- Data Governance: Practical experience implementing governance frameworks, lineage tracking, metadata management, and compliance.
- Architect scalable MLOps pipelines using Azure ML, MLflow, Databricks Asset Bundles (DAB), and CI/CD/CT
Good-to-Have.
- Design & deploy LLM solutions (RAG, Agentic AI, MCP, prompt engineering).
- Build Power BI dashboards for monitoring models and reporting business KPIs.
- Strong grounding in statistics, hypothesis testing, and data interpretation.
- Apply software engineering principles for reusable, testable, and maintainable ML code.
- Stay up to date with Generative AI, Agentic AI, and LLMs and assess practical adoption.
- Mentor juniors, review code, and conduct technical knowledge-sharing sessions.
- Certification: Microsoft Certified: Azure Data Scientist Associate (nice to have).
What We Offer:
- Competitive Salary
- Work Life Balance
Professional Development - Innovative Work Environment.
- Recognition and Rewards
Location:
IN-GJ-Ahmedabad, India-Ognaj (eInfochips)Time Type:
Full timeJob Category:
Engineering ServicesSkills
- Agentic AI
- AI
- AWS
- Azure
- Big Data
- CI/CD
- Cloud
- Data Governance
- Data Modeling
- Data Warehousing
- Databricks
- Deep Learning
- Feature Engineering
- GCP
- Generative AI
- Hadoop
- Kafka
- Keras
- LLM
- Machine Learning
- MCP
- Metadata Management
- MLflow
- MLOps
- Model Evaluation
- NoSQL
- NumPy
- pandas
- Power BI
- Prompt Engineering
- Python
- PyTorch
- RAG
- Reinforcement Learning
- scikit-learn
- Spark
- SQL
- Statistics
- TensorFlow