Senior AI / ML Engineer 

Production Systems & Deep Learning Platforms

(Reports to VP of Application Development,  Flexible Location - CST and EST preferred)

When an organization is ready to transform its AI engine from hopeful prototypes into real-world momentum, it needs someone who can bridge deep learning mastery with production discipline. This role exists to accelerate delivery, sharpen model performance, and guide advanced AI systems into the messy, beautiful world where people depend on them.

You'll shape specialized LLMs through reinforcement-learning insights, architect synthetic data pipelines that teach models how to thrive in production, and design feedback systems that help models evolve long after deployment. If you're energized by turning frontier AI into stable, scalable products, you'll thrive here.

What You'll Own

• Build automated, resilient deployment and monitoring frameworks for ML & DL models operating at scale.

• Engineer sophisticated synthetic data generation workflows that accelerate training and real-world readiness.

• Partner with engineering and product leads to translate business needs into secure, scalable AI architectures.

• Design, train, and optimize deep learning systemsespecially transformer-based models and LLMsusing modern reinforcement learning and adaptive fine-tuning methods.

• Architect and maintain advanced Databricks pipelines end-to-end (data ingestion, feature engineering, MLflow tracking, orchestration, deployment).

• Develop proofs-of-concept that illuminate business value and pave the way for production adoption.

• Own the lifecycle of solutions from initial concept through deployment, governance, monitoring, and iteration.

• Build automated CI/CD workflows supporting continuous model, data, and code evolution.

• Diagnose and resolve issues within live AI environments with technical precision and calm urgency.

• Collaborate across AI, data, software, and DevOps teams to ensure alignment and operational success.

What Success Looks Like

• AI systems consistently performing in production just scientifically sound, but operationally durable.

• Seamless integration of deep learning and machine learning components into analytics and operational workflows.

• LLMs tuned with measurable impact, governed effectively, and delivering meaningful outcomes.

• Automated and observable pipelines supporting the full lifecycle from ingestion to inference.

• Reliable AI-driven enhancements across recommendation systems, language understanding, image interpretation, and more.

What You Bring

• 7+ years of professional engineering experience focused on ML/AI systems.

• Bachelor's degree in a technical field or equivalent real-world mastery.

• Strong Azure cloud experience and expert-level Databricks skills across Delta, MLflow, clusters, compute management, and orchestration.

• Deep learning proficiency, including LLMs, neural architectures, optimization strategies, NLP methods, and evaluation frameworks.

• Python development strength across prototypes, pipelines, and production codebases.

• Ability to explain highly technical concepts with claritytailored to both engineering and business audiences.

• Security-first mindset with comfort operating in compliance-sensitive environments.

• Reliability within a 24/7 support rotation and genuine ease working across teams.

• Curiosity, humility, and an appetite for pushing generative AI further into practical impact.

Cultural Principles That Guide the Work

Certainty.
Deliver with precision and transparency. Honor commitments. Build trust through reliable execution.

Compassion.
Let real human challenges shape the work. Treat team members, partners, and end users with respect and empathy.

Advancement.
Pursue innovation with courage. Tell the truth. Move the organization forward with integrity.

About the Organization

This organization operates at the intersection of healthcare, technology, and long-term condition support, serving individuals across the country who rely on consistent, high-quality care beyond the clinic walls. Their model blends human expertise with AI-driven insights to improve outcomes, reduce avoidable costs, and support people managing complex health needs.

The organization has earned recognition for workplace excellence and maintains a strong research-driven approach to validating its impact. At its core, the team is committed to compassionate delivery, data-informed innovation, and improving health journeys at scale.