Bangalore, Karnataka, India
Information Technology
Full-Time
CapeStart
Overview
Key Responsibilities
- Lead End-to-End ML Projects: Own the full lifecycle of ML solutions from problem scoping, data exploration, model development, deployment, and post-deployment monitoring.
- Own the Gen AI Strategy: Define and drive the technical vision and execution strategy for Gen AI use cases across the organization.
- Architect Scalable Solutions: Design robust ML systems and pipelines that integrate seamlessly into production environments.
- Team Leadership: Mentor and guide a team of ML engineers and data scientists, fostering a culture of technical excellence, innovation, and continuous learning.
- Modeling & Research: Stay up to date with the latest advancements in ML/AI and guide experimentation with novel algorithms (e.g., deep learning, NLP, GenAI, reinforcement learning).
- Build RAG & Prompt Engineering Pipelines: Design scalable architectures for RAG, vector search, prompt tuning, and prompt chaining with tools like LangChain, LlamaIndex, and FAISS.
- Stakeholder Collaboration: Work closely with product managers, engineers, and domain experts to translate business problems into technical solutions.
- Operationalize ML: Partner with MLOps/DevOps teams to deploy, monitor, and maintain ML models in production, ensuring reliability and scalability.
- Bachelors or Masters degree in Computer Science, Machine Learning, Data Science, or related field (PhD is a plus).
- 8+ years of hands-on experience in machine learning, with at least 12 years in a leadership or mentorship role.
- Proficiency in Python and ML libraries such as scikit-learn, TensorFlow, PyTorch, HuggingFace Transformers, etc.
- Strong understanding of statistics, optimization, and model evaluation techniques.
- Experience with cloud platforms (AWS, GCP, or Azure) and tools like Docker, Kubernetes, MLflow, or Kubeflow.
- Proficiency in Python and Gen AI frameworks such as LangChain, Crew AI, or similar.
- Proven track record of deploying ML models into production at scale.
- Excellent communication and leadership skills.
- Background in domain-specific ML (e.g., healthcare, fintech, manufacturing).
- Familiarity with data engineering tools like Apache Spark, Airflow.
- Prior experience in startup or fast-paced environments.
- Artificial Intelligence, Natural Language Processing, machine learning, Deep Learning, Scikit-Learn, Python, Pytorch, Tensorflow, data science, Huggingface, Transformers, Langchain, Crew AI, Aws Cloud, Gcp Cloud, Azure Cloud.
- Background in domain-specific ML (e.g., healthcare, fintech, manufacturing).
- Familiarity with data engineering tools like Apache Spark, Airflow.
- Prior experience in startup or fast-paced environments
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