StatusNeo - ML Engineer
Nexthire
- Gurgaon, Haryana
- Permanent
- Full-time
Location: Bangalore (On-site – 5 Days a Week)
Employment Type: Full-TimeAbout the Role:We are looking for a highly experienced and driven ML Engineer with a strong background in Generative AI, Large Language Models (LLMs), and machine learning systems. This is a critical role where you will help design, build, and optimize advanced AI/ML solutions that power intelligent products and platforms.As a senior member of the AI team, you will work on state-of-the-art NLP models, contribute to the architecture of GenAI systems, and bring research to production in a fast-paced and collaborative environment.Key Responsibilities:
- Design and implement scalable AI/ML models, with a focus on LLMs and Generative AI use cases.
- Fine-tune and deploy foundation models (e.g., GPT, LLaMA, Mistral) using Python and modern ML frameworks.
- Lead research, experimentation, and prototyping of new ML algorithms and NLP approaches.
- Collaborate with data scientists, MLOps engineers, and product teams to integrate AI capabilities into real-world applications.
- Develop APIs and end-to-end ML pipelines for training, testing, and deployment.
- Stay current with emerging trends in artificial intelligence and apply best practices in production environments.
- 9+ years of experience in Artificial Intelligence, Machine Learning, and Python programming.
- Hands-on expertise in Generative AI and Large Language Models (LLMs).
- Strong knowledge of frameworks such as PyTorch, TensorFlow, and Hugging Face Transformers.
- Experience with prompt engineering, fine-tuning, and inference optimization of LLMs.
- Solid understanding of NLP, deep learning architectures, and model performance evaluation.
- Experience working with vector databases (FAISS, Pinecone) and retrieval-augmented generation (RAG) architectures.
- Proven ability to translate complex research into scalable applications.
- Exposure to LangChain, OpenAI APIs, Anthropic Claude, or other commercial LLM ecosystems.
- Familiarity with cloud platforms (AWS/GCP/Azure) and MLOps practices (Docker, MLFlow, CI/CD).
- Prior experience mentoring junior engineers or leading AI project teams.
- Contributions to open-source AI projects or published research in the AI/ML domain.