Senior Applied Scientist

RESPONSIBILTIES:

• Partner closely with customers to understand their vision, define requirements, and deliver AI solutions that remove blockers and unlock value. Dive deep into model architectures to maximize performance, scalability, and reliability.
• Build state-of-the-art solutions using emerging Gen AI and ML technologies.
• Configure and optimize large-scale OpenSearch clusters, including ingestion pipelines for high-volume data.
• Diagnose and resolve challenges in AI model training, deployment, and serving.
• Create reusable solution patterns and reference architectures that accelerate adoption across multiple customers.
• Act as a product evangelist showcasing our innovations at customer meetings, industry events, and conferences.
• Collaborate with world-class scientists, engineers, and product managers in a fast-moving, high-impact environment.

Qualifications

• Bachelor s or Master s degree in Computer Science or related technical field, with 6+ years of experience in AI, ML, or data-driven solution development.
• Proven track record designing, building, and deploying scalable AI/ML solutions in production environments.
• Deep expertise in Large Language Models (LLMs), Generative AI, Agentic solutions, and advanced ML techniques (fine-tuning, prompt engineering, model optimization).
• Strong experience with OpenSearch, vector databases, data ingestion pipelines, and large-scale search optimization.
• Skilled in diagnosing, troubleshooting, and resolving issues in AI model training and serving.
• Hands-on experience with NLP, NLU, RAG architectures, Agents, and modern AI frameworks (e.g., LangChain, LlamaIndex).
• Proficient in Python and shell scripting, with familiarity in deep learning frameworks (PyTorch, TensorFlow, JAX, or Transformers).
• Experience with popular model training and serving frameworks like KServe, KubeFlow, Triton etc.
• Excellent communication skills for translating complex technical concepts into clear proposals, designs, and presentations.
• Collaborative mindset with experience working closely with product managers, engineers, and customers.
• Ability to mentor and guide junior data scientists or ML engineers.
• Experience acting as a technical evangelist, presenting at conferences, customer briefings, or industry events.