This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff ML Engineer (ML/AI) based in United States.
This is a high-impact technical leadership role shaping the architecture and long-term direction of enterprise-scale machine learning and generative AI systems.
You will define platforms that enable teams to build, deploy, evaluate, and operate AI solutions safely, reliably, and efficiently.
The role combines deep hands-on engineering with strategic influence across engineering, data science, product, security, and clinical or domain leadership.
You will tackle complex, high-stakes problems and translate them into scalable AI capabilities and clear technical roadmaps.
Your work will help establish engineering standards across the full ML/AI lifecycle, from data lineage and model development through production monitoring.
You will also mentor senior engineers, influence architectural decisions, and raise the technical bar across the broader organization.
This is an opportunity to make a meaningful impact in a mission-driven environment while working on modern AI infrastructure and generative AI technologies.
Accountabilities:
- Define and execute the long-term architecture and roadmap for machine learning and generative AI platforms, enabling the rapid, secure, and reliable deployment of advanced models.
- Architect end-to-end AI infrastructure covering model training, fine-tuning, low-latency inference, centralized RAG systems, vector databases, and enterprise evaluation and guardrail frameworks.
- Establish engineering standards across the AI/ML software development lifecycle, including dataset lineage, CI/CD, automated model evaluation, red-teaming, observability, and production monitoring.
- Partner with product, data science, security, and domain experts to translate strategic business and clinical objectives into scalable AI platform capabilities.
- Provide technical leadership through architectural reviews, high-impact prototypes, critical-path development, and strategic coding contributions.
- Mentor senior machine learning engineers and help establish engineering practices that improve technical quality, scalability, reliability, and delivery across teams.
- Serve as a technical anchor across engineering and data organizations, building alignment around complex architectural and technology decisions.
Requirements:
- 8+ years of experience designing and deploying complex ML/AI solutions in mission-critical production environments, with demonstrated technical leadership.
- Advanced software and systems engineering expertise, including Python, RESTful API design, Protobuf, and microservices architectures.
- Strong hands-on experience with production ML/AI infrastructure, including Docker, Kubernetes, container orchestration, and real-time inference services.
- Proven experience designing modern generative AI systems, including RAG pipelines, LLM fine-tuning, vector databases, and robust evaluation and guardrail frameworks.
- Strong knowledge of data-layer technologies, including relational databases, low-latency key-value stores, distributed queueing systems such as Kafka or Celery, and data pipeline orchestration.
- Experience architecting cloud-native systems on AWS or comparable cloud platforms.
- Exceptional communication and strategic problem-solving skills, with the ability to turn ambiguous technical challenges into clear priorities and influence senior stakeholders across engineering, product, and business functions.
- Experience with Java or Kotlin is a plus, particularly for high-performance production systems.
- Experience working with AI/ML systems in regulated or highly sensitive environments, including HIPAA, SOC 2, PHI, or PII, is preferred.
- Experience building internal developer platforms, ML tooling, or infrastructure products adopted by multiple data scientists and engineers is highly valued.
- A collaborative, mission-driven mindset and enthusiasm for working across disciplines with technical and domain experts.
Benefits:
- Annual base salary of $161,000–$221,500, depending on skills, qualifications, experience, location, and other job-related factors.
- Potential eligibility for discretionary bonuses.
- Comprehensive healthcare coverage, including medical, dental, vision, FSA/HSA, life, and disability insurance.
- Access to coaching and therapy services.
- Equity through discretionary restricted stock units.
- Competitive paid time off, including vacation, sick days, and company holidays.
- Paid parental leave.
- 401(k) plan with up to 3% employer matching.
- Monthly technology allowance.
- Well-being perks, community activities, recognition initiatives, and additional employee experiences.
- Remote work environment with opportunities to collaborate across multidisciplinary teams.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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