
AI/ML Engineer
2 weeks ago
We're Hiring: AI/ML Engineer – GenAI & MLOps Focus.
Job Locations: Pune & Greater Noida Only.
Experience Required: 3 to 6 Years
Company: Coforge Ltd.
At Coforge Ltd. , we are looking for a passionate and skilled AI/ML Engineer with a strong foundation in machine learning, MLOps, and Generative AI. This role is ideal for professionals with 3 to 6 years of experience who are eager to work on real-world AI applications, including LLMs, NLP, Computer Vision, and Conversational AI .
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For queries, reach out via WhatsApp:
✅ Key Skills Required
Core AI/ML Skills:-
- End-to-end AI/ML solution design and architecture
- Model development, deployment, and monitoring (MLOps)
- Experience with:
- Natural Language Processing (NLP)
- Computer Vision
- Speech & Conversational AI
- Document AI
- Generative AI & LLMs (e.g., LangChain, custom LLMs)
Programming & Frameworks:-
- Languages: Python, Java
- ML Frameworks: TensorFlow, PyTorch, Keras, Scikit-learn
- NLP Tools: NLTK, SpaCy, Gensim
- API Frameworks: FastAPI, Flask, Django
Cloud & MLOps:-
- Cloud Platforms: AWS, Azure, GCP
- MLOps Tools: Kubeflow, MLflow
- Workflow Orchestration: Apache Airflow
AI System Design:-
- Neural Network Architectures: SVM, CNN, RNN, Transformers, Ensemble Models
- Vector Databases (for LLMs and RAG)
- Microservices Architecture
- Responsible AI Practices
Databases
- SQL: PostgreSQL
- NoSQL: MongoDB, Neo4j
Soft Skills
- Strong communication
- Technical leadership and mentorship
- Cross-functional collaboration
- Documentation and knowledge transfer
What We’re Looking For
- 3 to 6 years of hands-on experience in AI/ML
- Proven ability to design and deploy production-grade AI systems
- Proficiency in MLOps for scalable and maintainable pipelines
- Experience with Cognitive AI (NLP, Vision, Speech)
- Hands-on with LLMs and Generative AI is a big plus
- Cloud-native mindset with experience in AWS, Azure, or GCP
- Strong team player with leadership potential
- Passion for staying updated with the latest in AI/ML and GenAI
- Ability to collaborate across teams and drive AI adoption
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