AI ML Specialist Lead

We are seeking a cross-functional expert at the intersection of

Product, Engineering, and Machine Learning

to lead and build cutting-edge AI systems. This role combines the strategic vision of a Product Manager with the technical expertise of a Machine Learning Engineer and the innovation mindset of a Generative AI and LLM expert.You will help define, design, and deploy

AI-powered features

, train and fine-tune models (including LLMs), and architect intelligent AI agents that solve real-world problems at scale.

🎯 Key Responsibilities

🧩 Product Management:

Define product vision, roadmap, and AI use cases aligned with business goals.Collaborate with cross-functional teams (engineering, research, design, business) to deliver AI-driven features.Translate ambiguous problem statements into clear, prioritized product requirements.

⚙️ AI/ML Engineering & Model Development

Develop, fine-tune, and optimize ML models, including LLMs (GPT, Claude, Mistral, etc.).Build pipelines for data preprocessing, model training, evaluation, and deployment.Implement scalable ML solutions using frameworks like

PyTorch

,

TensorFlow

,

Hugging Face

,

LangChain

, etc.Contribute to R&D for cutting-edge models in GenAI (text, vision, code, multimodal).

🤖 AI Agents & LLM Tooling

Design and implement autonomous or semi-autonomous

AI Agents

using tools like

AutoGen

,

LangGraph

,

CrewAI

, etc.Integrate external APIs, vector databases (e.g., Pinecone, Weaviate, ChromaDB), and retrieval-augmented generation (RAG).Continuously monitor, test, and improve LLM behavior, safety, and output quality.

📊 Data Science & Analytics

Explore and analyze large datasets to generate insights and inform model development.Conduct A/B testing, model evaluation (e.g., F1, BLEU, perplexity), and error analysis.Work with structured, unstructured, and multimodal data (text, audio, image, etc.).

🧰 Preferred Tech Stack / Tools

Languages:

Python, SQL, optionally Rust or TypeScript

Frameworks:

PyTorch, Hugging Face Transformers, LangChain, Ray, FastAPI

Platforms:

AWS, Azure, GCP, Vertex AI, Sagemaker

ML Ops:

MLflow, Weights & Biases, DVC, Kubeflow

Data:

Pandas, NumPy, Spark, Airflow, Databricks

Vector DBs:

Pinecone, Weaviate, FAISS

Model APIs:

OpenAI, Anthropic, Google Gemini, Cohere, Mistral

Tools:

Git, Docker, Kubernetes, REST, GraphQL

🧑‍💼 Qualifications

Bachelor’s, Master’s, or PhD in Computer Science, Data Science, Machine Learning, or a related field.10+ years of experience in core ML, AI, or Data Science roles.Proven experience building and shipping AI/ML products.Deep understanding of LLM architectures, transformers, embeddings, prompt engineering, and evaluation.Strong product thinking and ability to work closely with both technical and non-technical stakeholders.Familiarity with GenAI safety, explainability, hallucination reduction, and prompt testing, computer vision

🌟 Bonus Skills

Experience with autonomous agents and multi-agent orchestration.Open-source contributions to ML/AI projects.

Prior Startup Or High-growth Tech Company Experience.

Knowledge of reinforcement learning, diffusion models, or multimodal AI.Skills: text,claude,vision,hugging face transformers,sagemaker,hallucination reduction,langchain,genai safety,machine learning,data science & analytics,transformers,crewai,gcp,open-source contributions to ml/ai projects,startup,chromadb,graphql,pipelines,diffusion models,llm architectures,prompt engineering,gpt,weaviate,cohere,structured, unstructured, and multimodal data,docker,autogen,ai/ml products,model development,git,ai use,a/b testing,core ml,code,ai/ml engineering & model development,vertex ai,architect intelligent ai agents,tensorflow,bleu,ai-driven features,error analysis,roadmap,typescript,retrieval-augmented generation (rag),model training,multimodal ai,weights & biases,image,generative ai,hugging face,ray,f1,explore and analyze large datasets,spark,kubernetes,data science,product management,autonomous agents,mlflow,multimodal,ai,rest,google gemini,model evaluation,computer vision,mistral,vector databases,sql,engineering,airflow,output quality,pinecone,langgraph,reinforcement learning,pandas,llms,rust,ai-powered features,fastapi,multi-agent orchestration,embeddings,python,aws,ml models,kubeflow,pytorch,azure,dvc,openai,faiss,databricks,audio,ai engineering,numpy,anthropic,define product vision