Sr Engineer, AI Solutions
Role details
Job location
Tech stack
Job description
- Design and implement AI/Machine Learning (ML) solutions across domains such as computer vision and Natural Language Processing (NLP), and Generative AI (GenAI) use cases: document understanding, summarization, and chatbots.
- Develop and optimize autonomous AI agents and related workflows, including integration with enterprise systems.
- Guide data labeling strategies and human-in-the-loop feedback for supervised and reinforcement learning models.
- Fine-tune and evaluate Large Language Models (LLMs), and implement GenAI patterns like prompt engineering, embeddings, vector stores, and Retrieval-Augmented Generation (RAG).
- Build and optimize robust data pipelines for large datasets, including data cleaning, transformation, labeling, and feature engineering.
- Design scalable APIs and real-time/batch inferencing services for AI capabilities use across teams and applications.
- Deploy and manage AI models using containerization, orchestration and Machine Learning Operations (MLOps) best practices (Continuous Integration and Deployment (CI/CD) pipelines on AWS and/or GCP).
- Collaborate with stakeholders to understand business needs, translate into AI solutions, and align with product goals and regulatory constraints.
- Mentor junior engineers in AI/Machine Learning (ML) fundamentals, coding standards, and deployment best practices.
- Contribute to research and innovation initiatives and evaluate new techniques, tools, and architectures in AI and ML.
- Other duties and responsibilities as assigned.
Requirements
The Senior Engineer, AI Solutions collaborates with cross-functional teams to design, develop, and deploy innovative AI solutions in areas such as computer vision and Large Language Models (LLMs). The role requires advanced technical expertise, a passion for innovation, and the ability to mentor junior engineers., * Master's degree in Computer Science, Data Science or related discipline from an accredited college or university. In lieu of degree, 6+ years of experience in AI/Machine Learning, and system design.
- 4+ years of experience in AI/Machine Learning engineering, working with system design and deployment of AI Solutions; practical experience in healthcare AI applications.
- 1+ years of advance technical expertise.
- Proficiency in Python and libraries such as TensorFlow, PyTorch, Hugging Face Transformers, or LangChain.
- Experience with GenAI and Large Language Models (LLMs), including fine-tuning and prompt engineering.
- Experience with retrieval-augmented generation (RAG), and vector databases.
- Experience with SQL and/or NoSQL databases for structured and unstructured data.
- Experience with cloud platforms (AWS and/or GCP).
- Experience with containerization (Docker) and orchestration (Kubernetes).
- Experience working in cross-functional teams.
Preferred
- 8+ years of experience in AI/Machine Learning (ML) with large-scale system design.
- Strong understanding of AI system design, scalability, and performance optimization.
- Experience with medical image analysis.
- Experience with React or other modern JavaScript frameworks.
- Experience with MLOps, CI/CD, and AI model optimization.
- Familiarity with HIPAA and healthcare compliance standards.
- Experience with clinical studies and statistical analysis.
Knowledge/Skills/Abilities
- Demonstrated interpersonal, verbal and written communication skills.
- Ability to collaborate with team members at all levels of the organization.
- Demonstrated ability to mentor and lead AI projects.
- Ability to adhere to industry best practices and regulatory requirements, particularly regarding data privacy and security.
- Familiarity with CI/CD pipelines and DevOps practices.
Benefits & conditions
Tuition reimbursement, 401(k), Health insurance, Paid time off, Vision insurance, Dental insurance, * Medical, dental, and vision insurance
- Paid time off
- Tuition Reimbursement
- 401K
- Paid time to volunteer in your local community