Data Scientist Senior Associate - Applied AI ML
Posted May 7, 2026
Key Responsibilities:
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Lead the hands-on design, development, and deployment of advanced AI, GenAI, and large language model solutions. - Serve as a subject matter expert on a wide range of machine learning techniques and optimizations. - Collaborate with product, engineering, and business teams to deliver scalable, production-ready AI systems. - Conduct experiments using the latest ML technologies, analyze results, and tune models for optimal performance. - Own end-to-end code development in Python for both proof-of-concept and production-ready solutions. - Integrate generative AI within the ML platform using state-of-the-art techniques. - Drive adoption of modern ML infrastructure, tools, and best practices. - Optimize system accuracy and performance by identifying and resolving inefficiencies. - Communicate technical concepts and results to both technical and business stakeholders. - Ensure responsible AI practices, model governance, and compliance with regulatory standards. - Mentor and guide other AI engineers and scientists, fostering a culture of continuous learning. Qualifications Required:
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Masters or PhD in Computer Science, Engineering, Mathematics, or a related quantitative field. - Minimum 5 years of hands-on experience in applied machine learning, including generative AI, large language models, or foundation models. - Experience programming in Python; experience with ML frameworks such as PyTorch or TensorFlow. - Proven experience designing, training, and deploying large-scale ML/AI models in production environments. - Deep understanding of prompt engineering, agentic workflows, and orchestration frameworks. - Experience with cloud platforms (AWS, Azure, GCP) and distributed systems (Kubernetes, Ray, Slurm). - Solid grasp of MLOps tools and practices (MLflow, model monitoring, CI/CD for ML). - Strong communication skills with the ability to explain complex technical concepts to diverse audiences. - Demonstrated leadership in working effectively with engineers, product managers, and other ML practitioners. - Experience applying data science and ML techniques to solve business problems and passion for detail, follow-through, and technical excellence. Key Responsibilities: