Tech Lead

Develop novel, scalable AI powered solutions related to all the above-mentioned areas.Train Deep Learning / Transformer based models for different classification tasks.Evaluate, fine-tune and leverage LLMs / GenerativeAI models to address different use cases .Plan and execute cutting-edge research and prototyping

Work on end-2-end ML workflow life-cycle (MLOps, CI/CD, A/B Testing) and various related frameworks/tools (e.g., MLFlow).

Min Qualification BSc in Computer Science and MSc with strong GPA in Machine Learning, or related technical fields

4+ years of industry experience on developing and deploying efficient ML/AI models and services in real-world environments.

Strong engineering skills and proficiency in Python

Solid foundation in Machine Learning with engineering experience in some of the following relevant specialization areas Text Mining, Natural Language Processing (NLP), Natural Language Understanding (NLU), Representation Learning, Information Retrieval & Content-based Recommendation, GenerativeAI, Information Extraction, NER & Entity Linking

Experience with various deep learning and ML frameworks such as PyTorch, HuggingFace Transformers, spaCy, scikit-learn,

Experience with end-2-end ML workflow life-cycle (MLOps, CI/CD, A/B Testing) and various related frameworks/tools (e.g., MLFlow)

Experience with Python backend APIs / development frameworks also supporting long running tasks (e.g., FastAPI, Celery), microservices architecture, IoC/DI patterns and containerization

Experience with Git, Jira, Cloud Build or Jenkins

Excellent problem solving and analytical skills

A passion for Machine Learning & AI-powered solutions

Strong sense of ownership, urgency and drive

Military obligations fulfilled for male candidates

Preferred Qualifications Experience with scalable and interoperable ML models and inference servers (e.g., ONNX, NVidia Triton, HF Text Generation Inference (TGI))

Familiarity with Cloud technologies (especially Google Cloud)

Background and experience with one or more of the following technologies

Distributed Data Processing using ApacheSpark

Text-based / vector-based search Engines (e.g.,ElasticSearch, FAISS, etc)

Streaming and batch processing data pipelines (Apache Beam / GCP DataFlow)

Good understanding of Agile methodologies