All openings
Engineering•Full-time
AI/ML Engineer
Build the models that power real products, at real scale.
IndiaRemote2–5 years of experienceCompensation₹6 LPA
About the role
We're looking for an AI/ML Engineer who thrives on turning ambiguous business problems into reliable, production-grade machine-learning systems.
You'll own the full lifecycle—from data pipelines and model development through deployment, monitoring, and iteration—working closely with product, data, and engineering teams to ship AI that actually moves the needle.
Core skills
PythonPyTorch / TensorFlowLLMs & RAGPrompt EngineeringMLOpsAWS / Azure / GCPSQLTransformersModel DeploymentCI/CDGenerative AIDocker & Kubernetes
What you’ll do
- Design, train, and fine-tune ML and LLM-based models to solve specific product and business problems.
- Build and maintain end-to-end ML pipelines covering data ingestion, feature engineering, training, evaluation, and deployment.
- Deploy and scale models in production using MLOps best practices such as CI/CD, monitoring, versioning, and rollback.
- Apply LLMs, RAG architectures, and prompt engineering to build intelligent, context-aware features.
- Optimize model performance, latency, and cost across cloud infrastructure.
- Collaborate cross-functionally to translate business requirements into technical specifications.
- Monitor deployed systems for drift, reliability, and fairness, then iterate responsibly.
What we’re looking for
- 2–5 years of experience building and deploying machine-learning models in production.
- Strong proficiency in Python and hands-on experience with PyTorch or TensorFlow.
- Solid understanding of transformer architectures, attention mechanisms, and modern LLMs such as GPT, BERT, or T5.
- Practical experience with RAG pipelines, vector databases, and prompt engineering.
- Working knowledge of MLOps tooling including Docker, Kubernetes, CI/CD, and model registries.
- Comfortable with SQL, relational databases, and at least one major cloud platform: AWS, Azure, or GCP.
- Strong software engineering fundamentals including testing, version control, code review, and documentation.
- Excellent problem-solving instincts and the judgment to ship pragmatically, not just experiment endlessly.
- Bachelor's or Master's in Computer Science, Data Science, ML, or a related field—or equivalent hands-on experience.
Nice to have
- Experience with generative AI products or applied research shipped to real users.
- Exposure to responsible AI practices such as bias auditing, model explainability, and fairness testing.
- Contributions to open-source ML projects or published technical writing.
What Codvera offers
- Own real ML systems end-to-end—not just notebooks that never ship.
- Work with a team that treats AI as a product discipline, not a research side project.
- Competitive compensation, flexible remote-friendly setup, and a clear growth path.