AI/ML Software Engineer
Jumbo Consulting
3 - 5 years
Bengaluru
Posted: 13/06/2026
Job Description
Location: Marathahalli, Bangalore (In-Office)
Experience: 13 Years
Compensation: Up to 20 LPA (including variable) + ESOPs
Industry: AI Infrastructure / Enterprise AI
About the Role
We are looking for an AI/ML Software Engineer to join a fast-growing AI company building next-generation enterprise AI solutions. You will work closely with engineering and product teams to build, deploy, and optimise machine learning systems used in real-world production environments.
Key Responsibilities
- Build, train, evaluate, and deploy machine learning models for production use cases.
- Develop scalable backend services and APIs to support AI-powered applications.
- Work with large datasets to improve model accuracy and performance.
- Collaborate with product and engineering teams to translate business requirements into AI solutions.
- Optimise model inference, latency, and infrastructure costs.
- Implement monitoring, testing, and observability for AI systems.
- Stay updated with the latest developments in LLMs, Generative AI, and machine learning.
Requirements
- 13 years of experience in Software Engineering, Machine Learning, or AI-related roles.
- Strong programming skills in Python.
- Experience with machine learning frameworks such as PyTorch, TensorFlow, or Scikit-learn.
- Understanding of data structures, algorithms, and software engineering fundamentals.
- Familiarity with REST APIs, cloud platforms, and modern development practices.
- Experience working with databases and data pipelines.
- Strong problem-solving and communication skills.
Preferred Qualifications
- Experience with LLMs, RAG systems, or Generative AI applications.
- Familiarity with AWS, Docker, and Kubernetes.
- Experience deploying ML models in production environments.
- Exposure to vector databases and modern AI tooling.
What Youll Get
- Up to 20 LPA (including variable) plus ESOPs.
- Opportunity to work on cutting-edge AI products.
- Fast-paced startup environment with significant ownership.
- Exposure to real-world AI deployment challenges.
- Strong learning and growth opportunities.
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