Machine Learning Engineer

Job Description

Title: Machine Learning Engineer Primary Location: Hyderabad/Trivandrum(Onsite) Job Type: Contract Secondary Location: Any Infosys Office Location In this position you will: • Design and implement NLP pipelines for document analysis and artifact generation. • Perform data cleaning and transformation on unstructured text using industry-standard techniques. • Develop embeddings and semantic search pipelines using OpenAI, HuggingFace, or custom models. • Integrate vectorized data with retrieval systems such as MongoDB Vector, FAISS or Pinecone. • Fine-tune and evaluate LLMs for use cases like test case generation, user story summarization, etc. • Monitor model performance and conduct regular evaluations with precision/recall/F1/BLEU. • Collaborate with backend developers to expose ML outputs via APIs. • Participate in architectural design and PoCs for GenAI-based solutions. • Adhere to and implement Responsible AI principles in all ML workflows. • Work closely with product owners and testers to ensure the quality and usability of generated outputs. Required Qualifications: • 5+ years of experience in in data science and AI/ML engineering with strong proficiency in Python and applied NLP • Deep expertise in NLP techniques including: Text classification, Named Entity Recognition (NER), Summarization, Sentiment analysis, Topic modeling • Strong experience in data preprocessing and cleaning :Tokenization, stop-word removal, stemming/lemmatization, normalization. • Strong Experience in vectorization methods: TF-IDF, Word2Vec, GloVe, BERT, Sentence Transformers. Demonstration experience of vectorization and implement solutions to contextual search is must • Hands on Experience in implementing Lang Chain, RAG architecture, and multi-agent orchestration, Agentic AI, scikit learn, python is must • Hands-on with embedding models (e.g., OpenAI, Hugging Face Transformers) and chunking strategies • Experience with vector stores: MongoDB atlas Vector DB, FAISS, Pinecone, Chroma DB. • Skilled in building and fine-tuning LLMs and prompt engineering is must • Experience with MLOps frameworks for model lifecycle, versioning, deployment, and monitoring. • Strong knowledge of LLMOps, NumPy, PySpark for data wrangling. • Experience deploying models on Azure (preferred), AWS, or GCP. • Understanding of Responsible AI practices including model fairness, transparency, and auditability. • Strong knowledge of machine learning frameworks, deep learning architectures, natural language processing and generative models (e.g., GANs, transformers). Preferred Qualifications: • 3 + years of experience building, scaling, and optimizing training and inferencing systems for deep neural networks and/or transformer architectures. • Demonstrated ability in research and development teams with a focus on generative AI technologies and suggesting new ideas or opportunities. • Experience in managing production scale pre training models (private or public cloud) or setting up GPU clusters for In house LLM deployments • Familiarity with AI Governance, ethics, compliance, and regulatory considerations. Education: • Bachelor’s degree or equivalent work experience in Computer Science, Engineering, Machine Learning, or related discipline. • Master’s degree or PhD preferred. Thanks Aatmesh aatmesh.singh@ampstek.com