HIRING ORGANIZATION : PyTorch India

SALARY : ₹20.0 – 35.0 LPA , EXPERIENCE : 5 years

ML Engineer job in Bangalore India :

LOCATION :Bangalore , India

Last Date : 12 September 2026.

The company is looking for a passionate and experienced Senior Machine Learning Engineer to join our growing AI/ML team. This is a hands-on role where you will be responsible for the entire lifecycle of machine learning models, from research and experimentation to deployment, scaling, and maintenance. You will play a pivotal role in building the core AI engine that powers our products, directly impacting the experience of millions of users.

This is not just a research position. We are looking for an engineer who loves to ship code and is obsessed with building robust, scalable, and maintainable ML systems. You will bridge the gap between data science and software engineering, ensuring our models are production-ready and deliver tangible business value.

Key Responsibilities

• Model Development & Deployment: Design, develop, and deploy state-of-the-art machine learning models, with a strong focus on Large Language Models (LLMs) and deep learning architectures. You will own the end-to-end process, from data collection and feature engineering to model training, validation, and serving.
• Production Engineering: Write clean, efficient, and testable Python code to build resilient and scalable microservices for model inference. You will architect and implement the infrastructure required to serve models in a low-latency, high-availability production environment.
• LLM Specialization: Lead the fine-tuning, prompting, and evaluation of LLMs for specific business use cases such as [e.g., text generation, summarization, sentiment analysis, question answering, and code generation]. You will explore and implement techniques like Retrieval-Augmented Generation (RAG) to enhance model performance.
• MLOps & Infrastructure: Champion best practices in MLOps. This includes setting up and maintaining CI/CD pipelines for models, monitoring model performance and data drift in production, and automating retraining processes.
• Collaboration & Mentorship: Work closely with cross-functional teams, including Product Managers, Data Scientists, and Software Engineers, to understand requirements and translate them into technical solutions. You will also mentor junior engineers and contribute to the team’s technical roadmap and best practices.
• Research & Innovation: Stay abreast of the latest advancements in AI/ML, particularly in the field of LLMs. Proactively identify opportunities to apply new techniques and technologies to improve our products and processes.

Required Skills & Qualifications

• Experience: 5+ years of professional experience in software engineering with a focus on machine learning. A Master’s or Ph.D. in Computer Science, AI, or a related field is a plus but not a requirement.
• Technical Proficiency:
  • Programming: Expert-level proficiency in Python.
  • Deep Learning: Deep, hands-on experience with PyTorch is mandatory. Experience with TensorFlow is a plus.
  • Large Language Models: Proven experience working with LLMs (e.g., GPT, Llama, Mistral, Gemini). This includes familiarity with the Hugging Face ecosystem, fine-tuning techniques (e.g., LoRA, QLoRA), and prompt engineering strategies.
  • MLOps: Strong understanding of cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes). Experience with MLflow, Weights & Biases, or similar experiment tracking tools is highly desirable.
• Software Engineering: Solid understanding of software engineering principles, including data structures, algorithms, design patterns, and API development (RESTful/gRPC). Experience with version control (Git) and CI/CD workflows.
• Problem-Solving: Exceptional analytical and problem-solving skills, with a demonstrated ability to break down complex business problems into tractable ML solutions.

Good to Have

• Experience with vector databases for RAG applications.
• Experience with distributed training and model parallelization.
• Contributions to open-source ML projects.
• Experience in [Insert specific domain, e.g., FinTech, Healthcare] is a plus.