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Senior Data Scientist – AI / Machine Learning
Location: Bay Area, CA
(Open/Hybrid)
Job Description
Role Overview
Experience: 9+ years
We are seeking a Senior Data Scientist with deep expertise in Artificial Intelligence (AI) and Machine Learning (ML) to design, build, and deploy advanced data-driven and AI-powered solutions. This role requires strong hands-on experience across the full ML lifecycle—from problem framing and data engineering through model development, deployment, and monitoring—along with the ability to work independently and lead complex initiatives.
The ideal candidate combines strong statistical foundations, modern ML/GenAI capabilities, and production-grade engineering skills, and can partner effectively with business, engineering, and leadership stakeholders.
Key Responsibilities
Lead end-to-end development of AI/ML solutions, including data exploration, feature engineering, model training, evaluation, and deployment
Design, develop, and optimize machine learning models such as regression, classification, clustering, NLP, and deep learning models
Build and deploy production-grade ML systems, ensuring scalability, performance, reliability, and cost efficiency
Develop Generative AI solutions including LLM-based applications, prompt engineering, RAG pipelines, and agentic workflows (where applicable)
Collaborate with data engineers to design and maintain robust data pipelines for structured and unstructured data
Perform model validation, experimentation, and performance monitoring, ensuring accuracy, fairness, and robustness
Translate complex analytical findings into clear business insights and recommendations for senior stakeholders
Mentor junior data scientists and provide technical leadership across projects
Contribute to AI governance, MLOps/LLMOps standards, documentation, and best practices
Partner cross-functionally with product, engineering, and business teams to deliver measurable business outcomes
Required Qualifications
9+ years of hands-on experience in Data Science, Machine Learning, or Applied AI
Strong proficiency in Python and common data science libraries (NumPy, pandas, scikit-learn)
Solid experience with ML frameworks such as PyTorch, TensorFlow, or Hugging Face
Strong understanding of statistics, probability, and experimental design
Experience building and deploying models in cloud environments (AWS, Azure, or GCP)
Hands-on experience with model deployment, monitoring, and MLOps tools (e.g., MLflow, CI/CD for ML)
Experience working with large datasets, SQL, and modern data stores
Excellent communication skills with the ability to explain technical concepts to non-technical audiences
Preferred / Nice-to-Have Skills
Experience with Generative AI and Large Language Models (LLMs)
Hands-on knowledge of RAG architectures, vector databases, and unstructured data pipelines
Familiarity with LLMOps, observability, and responsible AI practices
Experience in consulting or client-facing environments
Knowledge of big data technologies (Spark, Databricks)
Prior experience leading small teams or acting as a technical lead
Education
Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field
PhD is a plus but not required
Compétences linguistiques
- English
Avis aux utilisateurs
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