What are the responsibilities and job description for the Principal AI/ML Engineer with 15+ Years of experience MUST Needed position at New York Technology Partners?
Job Details
Role: Principal AI/ML Engineer
Location: Seattle, WA (Hybrid)
Duration: Long Term
Job Summary:
Overall, 12-15 Years with 5-6 years experience in AI/ML
Must have skill :
Python/Java, TensorFlow / PyTorch, LangChain, Hugging Face.
Hands-on with LLMs, embeddings, fine-tuning, and vector databases (FAISS, Pinecone, Chroma, etc.).
Familiarity with NLP, text summarization, classification, semantic search, and RAG pipelines.
Understanding of data engineering pipelines.
Role Overview:
We are seeking a seasoned Principal AI/ML Engineer to lead the design, development, and deployment of cutting-edge AI/ML solutions. This role requires a visionary leader who can define technical strategy, mentor teams, and drive innovation in Generative AI, LLMs, and advanced machine learning techniques.
Key Responsibilities -
- Architect AI/ML Solutions: Define and implement scalable AI/ML architecture, frameworks, and standards.
- End-to-End Model Lifecycle: Oversee data preparation, model training, deployment, and performance monitoring.
- MLOps Excellence: Build robust ML Ops pipelines and reusable components for production-grade systems.
- Leadership & Mentorship: Guide senior engineers and cross-functional teams to deliver impactful AI solutions.
- Innovation in Generative AI: Drive adoption of LLMs, Retrieval-Augmented Generation (RAG), and advanced ML methodologies.
- Governance & Compliance: Ensure adherence to AI governance, fairness, security, and ethical principles.
- Strategic Alignment: Collaborate with business and product leaders to align AI initiatives with organizational goals. Required Skills & Experience
- Technical Expertise:
o Strong proficiency in Python, TensorFlow/PyTorch, Scikit-learn, and Transformers.
o Hands-on experience with LLM fine-tuning, RAG, and vector databases (FAISS, Pinecone).
- MLOps & Cloud Platforms: o Proficient in MLflow, Airflow, Docker, Kubernetes.
o Experience with AWS SageMaker, Google Cloud Platform Vertex AI, or Azure ML.
- Data & Governance: o Deep understanding of data engineering, model governance, and AI ethics.
- Leadership Skills: o Excellent communication, stakeholder management, and ability to influence at all levels.
