Senior Machine Learning Engineer

About the Role

We are partnering with a fast-growing AI-driven technology company that is transforming one of the world’s largest and most traditional industries through advanced machine learning and automation. The company is building complex data and engineering workflows powered by cutting-edge AI — with LLMs, NLP, and Computer Vision at the core.

As a Senior Machine Learning Engineer , you will be a key technical owner driving end-to-end development of intelligent systems — from research and experimentation to production deployment. You’ll collaborate with product, data, and engineering teams to design and scale solutions that solve challenging real-world problems.

This is an exciting opportunity to join a high-growth environment where your work will directly impact digital transformation at a global scale.

Key Responsibilities

Research, design, and develop advanced AI models — from small classifiers to fine-tuned LLMs tailored for specific business use cases.

Build and deploy scalable NLP, CV, and RAG-based pipelines for extracting and structuring unstructured data.

Optimize performance, accuracy, and latency of deployed AI systems in production.

Operationalize efficient dataset creation, preprocessing, and management workflows .

Collaborate closely with cross-functional teams — engineering, data annotation, product, and leadership — to deliver AI-powered features.

Drive best practices in AI / ML development, model monitoring, and experimentation .

Mentor junior engineers and help establish strong ML engineering standards within the team.

Required Qualifications

Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.

5+ years of hands-on experience in machine learning and data science.

Proven experience with fine-tuning LLMs , building RAG pipelines , and integrating off-the-shelf or open-source LLMs.

Strong understanding of transformer architectures , embeddings, and optimization techniques.

Demonstrated expertise in NLP (semantic search, entity recognition, text classification, summarization).

Experience with Computer Vision (OCR, object detection, image classification).

Strong coding skills in Python and familiarity with ML libraries such as PyTorch, TensorFlow, Hugging Face, Spacy, NLTK, and Scikit-learn .

Hands-on experience managing large datasets and deploying AI models in production environments.

Solid understanding of data pipelines, APIs, and model lifecycle management .

Excellent problem-solving, analytical, and communication skills.

Preferred Qualifications

Experience with cloud-based ML platforms (AWS, GCP, or Azure) and containerization tools (Kubernetes, Docker).

Knowledge of MLOps practices including CI / CD, model monitoring, and versioning.

Experience with vector databases (FAISS, Pinecone, Chroma) and orchestration tools (Airflow, MLflow).

Exposure to web application architecture (Django, FastAPI) or AWS services (Bedrock, SageMaker).

Prior experience in OCR, PDF parsing , or document AI systems.

Contributions to open-source projects or publications in AI / ML research.

Experience working in high-growth, global product environments .

What’s on Offer

Competitive compensation with performance-based bonus

ESOPs and comprehensive health insurance (including family coverage)

Flexible working hours and hybrid setup

Unlimited paid time off

Learning and upskilling budget

Opportunity to grow in a rapidly scaling, innovation-focused company