Senior Machine Learning, Generative AI Engineer

Sustainable Talent is partnering with Nvidia a global leader who's been transforming computer graphics, PC gaming, and accelerated computing for over 25 years.  We are looking for a Senior Machine Learning, Generative AI Engineer to support our client's Digital Marketing platform, Team.  This is a W-2 full-time contract based in Santa Clara, CA with REMOTE work options. We offer competitive pay $100-$120/hr based on factors like experience, education, location, etc. and provide full benefits, PTO, and amazing company culture!

As an AI Engineer, you'll work alongside NVIDIA’s Digital Marketing platform team, dedicated to addressing our evolving data-driven marketing and compliance challenges. We value expertise in data science paired with a robust data engineering foundation. Together, we'll architect data pipelines, delve into sophisticated data analysis, and craft models using ML. Our focus includes Generative AI, large language models, Agentic AI systems, and their responsible deployment using security standards and performance optimization.

We seek someone proficient in programming and scripting for comprehensive data manipulation, analysis, and model creation. We thrive with working with Big Data technologies like Hadoop, Spark, and NoSQL databases, efficiently processing vast datasets. If you share a passion for innovation, secure AI development, and creating exceptional user experiences through intelligent systems, you're the one we've been searching for. We value proactive problem-solving, minimal direction, and teammates who collaborate, think, and learn together. Let's make a difference!

What you’ll be doing:

• Develop and implement ML and GenAI models: Design, develop, and deploy scalable machine learning and generative AI models—including LLMs and agentic systems—that address complex business challenges in the marketing and business domain (e.g., recommendation engines, intelligent assistants).
• Experiment and improve performance: Enhance existing recommendation systems and LLMs by optimizing model architecture, latency, and inference speed for real-world deployments at scale.
• Fine-tuning and prompt engineering: Customize foundation models using domain-specific datasets to improve accuracy and contextual relevance; design effective prompts for generative and retrieval-augmented generation (RAG) use cases.
• Implement guardrails and safety mechanisms: Ensure responsible AI usage by integrating moderation filters, response constraints, and behavior boundaries using frameworks like NVIDIA NeMo Guardrails or similar.
• AI security and compliance: Design AI systems with attention to data privacy, access control, prompt injection protection, and safe handling of critical marketing data.
• Build algorithms to understand user interest and intent, improve content relevancy, and support adaptive personalization strategies.
• Architect end-to-end solutions for complex data platforms and large-scale CI/CD data pipelines using a variety of technologies and data stores aligned with compliance needs.
• Collaborate with engineers and scientists to transform large, noisy datasets into training and evaluation datasets for model development and iteration.
• Collaborate multi-functionally with product managers, engineers, and analysts to translate business requirements into production-grade AI solutions.

What we need to see:

• Bachelor’s Degree in Computer Science or a related field or equivalent experience.
• Proven experience as a Machine Learning or AI Engineer with a track record of delivering ML and GenAI solutions.
• Solid understanding and hands-on experience with LLMs, GenAI frameworks, and Agentic AI tools (e.g., LangChain, CrewAI, AutoGen).
• Experience with fine-tuning, prompt optimization, and serving LLMs in a production environment.
• Familiarity with guardrails, content safety filters, and responsible AI practices (e.g., using NVIDIA NeMo Guardrails, moderation layers).
• Understanding of AI security practices, including prompt injection mitigation, safe API exposure, and privacy-aware model deployment.
• Working SQL knowledge and experience with relational/non-relational databases.
• Strong programming skills in Python, Golang, R, or Java; experience with ML frameworks like TensorFlow, PyTorch, scikit-learn.
• Ability to evaluate and tune models using robust metrics, A/B testing, and business impact measurement.

Ways to stand out from the crowd:

• Experience deploying and monitoring LLM or deep learning systems in production at scale.
• Proven ability to secure and govern GenAI systems, including audits, access control, and guardrail implementations.
• Experience optimizing LLM performance through quantization, distillation, or custom pipelines.
• Proficiency in RAG pipelines, semantic search, vector databases, and personalization through embeddings.
• Passion for staying abreast of the latest trends in GenAI, AI security, and responsible development practices.

Sustainable Talent is a M/F+, disabled, and veteran equal employment opportunity and affirmative action employer.