Posted:14 hours ago| Platform:
On-site
Full Time
AI Specialist / Machine Learning Engineer Location: On-site (hyderabad) Department: Data Science & AI Innovation Experience Level: Mid–Senior Reports To: Director of AI / CTO Employment Type: Full-time Job Summary We are seeking a skilled and forward-thinking AI Specialist to join our advanced technology team. In this role, you will lead the design, development, and deployment of cutting-edge AI/ML solutions, including large language models (LLMs), multimodal systems, and generative AI. You will collaborate with cross-functional teams to develop intelligent systems, automate complex workflows, and unlock insights from data at scale. Key Responsibilities Design and implement machine learning models for natural language processing (NLP), computer vision, predictive analytics, and generative AI. Fine-tune and deploy LLMs using frameworks such as Hugging Face Transformers, OpenAI APIs, and Anthropic Claude. Develop Retrieval-Augmented Generation (RAG) pipelines using tools like LangChain, LlamaIndex, and vector databases (e.g., Pinecone, Weaviate, Qdrant). Productionize ML workflows using MLflow, TensorFlow Extended (TFX), or AWS SageMaker Pipelines. Integrate generative AI with business applications, including Copilot-style features, chat interfaces, and workflow automation. Collaborate with data scientists, software engineers, and product managers to build and scale AI-powered products. Monitor, evaluate, and optimize model performance, focusing on fairness, explainability (e.g., SHAP, LIME), and data/model drift. Stay informed on cutting-edge AI research (e.g., NeurIPS, ICLR, arXiv) and evaluate its applicability to business challenges. Tools & Technologies Languages & Frameworks Python, PyTorch, TensorFlow, JAX FastAPI, LangChain, LlamaIndex ML & AI Platforms OpenAI (GPT-4/4o), Anthropic Claude, Mistral, Cohere Hugging Face Hub & Transformers Google Vertex AI, AWS SageMaker, Azure ML Data & Deployment MLflow, DVC, Apache Airflow, Ray Docker, Kubernetes, RESTful APIs, GraphQL Snowflake, BigQuery, Delta Lake Vector Databases & RAG Tools Pinecone, Weaviate, Qdrant, FAISS ChromaDB, Milvus Generative & Multimodal AI DALL·E, Sora, Midjourney, Runway Whisper, CLIP, SAM (Segment Anything Model) Qualifications Bachelor’s or Master’s in Computer Science, AI, Data Science, or related discipline 3–7 years of experience in machine learning or applied AI Hands-on experience deploying ML models to production environments Familiarity with LLM prompt engineering and fine-tuning Strong analytical thinking, problem-solving ability, and communication skills Preferred Qualifications Contributions to open-source AI projects or academic publications Experience with multi-agent frameworks (e.g., AutoGPT, OpenDevin) Knowledge of synthetic data generation and augmentation techniques Job Type: Permanent Pay: ₹734,802.74 - ₹1,663,085.14 per year Benefits: Health insurance Provident Fund Schedule: Day shift Work Location: In person
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