Senior MLOps Engineer - USA Onsite (Scottsdale, AZ)

S27a; Scottsdale (AZ); On-site; USD 170,000 - 250,000; Full time

Benefits offered by this job

Unlimited PTO

Competitive parental leave

Annual bonus program

Stock purchase program

Job summary

S27a is seeking a Senior AI/ML Engineer to lead production-grade ML systems and advance ML engineering and MLOps maturity. You will own critical ML workstreams end to end, make architectural decisions, mentor engineers, and collaborate with cross-functional teams.

The role demands deep technical expertise and production delivery experience. The ideal candidate will drive ML lifecycle, institute scalable pipelines, and shape the technical roadmap while ensuring systems are reliable and aligned

Qualifications

• Bachelor’s or Master’s in CS/Math/Stats; PhD a plus.
• 8–10 years of professional experience in ML engineering or production ML.
• Deep Python expertise and proficiency with ML frameworks TensorFlow, PyTorch, or JAX.
• Extensive experience designing and operating production ML pipelines at scale.
• Strong knowledge of MLOps principles and tools (MLflow, Kubeflow, Airflow, Argo Workflows or similar).
• Experience with cloud-native ML platforms (AWS SageMaker, Azure ML, GCP Vertex AI) and IaC practices.
• Experience with model serving at scale (TensorFlow Serving, Triton, BentoML, Seldon).
• Strong understanding of distributed computing, data engineering, and scalable system design.
• Experience with monitoring, observability, and governance for production ML systems.
• Demonstrated ability to mentor engineers and influence technical direction.
• Excellent communication skills with ability to present technical concepts to diverse audiences.

Responsibilities

• Lead design, development, and production deployment of ML systems across NLP, CV, recommendation, forecasting, etc.
• Own end-to-end ML lifecycle from problem framing to monitoring.
• Architect scalable, fault-tolerant ML pipelines with modern orchestration.
• Drive MLOps maturity, CI/CD for ML, automated retraining, model registry, governance.
• Define and enforce engineering standards for model development, testing, and docs.
• Evaluate new tools/frameworks to improve model performance and developer productivity.
• Collaborate with data/platform engineers and product teams to align ML infra.
• Mentor mid-level and junior engineers.
• Conduct design and code reviews and architectural assessments.
• Contribute to technical roadmap and communicate tradeoffs to leadership.
• Identify and mitigate data quality, drift, bias, and security risks.

Skills

Python

TensorFlow

PyTorch

JAX

ML engineering

MLOps

AWS SageMaker

Azure ML

GCP Vertex AI

Model serving

Distributed systems

Mentoring

Communication

Education

Bachelor’s or Master’s degree in CS/Math/Stats

PhD preferred

Tools

MLflow

Kubeflow

Airflow

Argo Workflows

Seldon

Triton

BentoML

Job description

About the Role

We are looking for a Senior AI/ML Engineer to lead the design and delivery of production-grade machine learning systems and drive the maturity of our ML engineering and MLOps capabilities. In this role, you will own critical ML workstreams end to end, make key architectural decisions, mentor other engineers, and collaborate closely with cross-functional teams to ensure ML solutions are scalable, reliable, and aligned with business objectives. The ideal candidate brings deep technical expertise, proven production experience, and the ability to influence technical direction across the team.

Key Responsibilities

• Lead the design, development, and production deployment of complex machine learning systems across multiple domains (NLP, computer vision, recommendation, forecasting, etc.).
• Own the end-to-end ML lifecycle from problem framing and data strategy through model development, validation, deployment, and monitoring.
• Architect scalable, fault-tolerant ML pipelines using modern orchestration and serving frameworks.
• Drive the adoption and maturity of MLOps practices including CI/CD for ML, automated retraining, model registry, and governance.
• Define and enforce engineering standards for model development, testing, code quality, and documentation.
• Evaluate and introduce new tools, frameworks, and techniques to improve model performance, pipeline efficiency, and developer productivity.
• Collaborate with data engineers, platform engineers, and product teams to align ML infrastructure with organizational goals.
• Mentor and provide technical guidance to mid-level and junior engineers.
• Conduct design reviews, code reviews, and architectural assessments for ML systems.
• Contribute to technical roadmap planning and communicate tradeoffs and recommendations to engineering leadership.
• Identify and mitigate risks related to data quality, model drift, bias, and security in production ML systems.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, or a related field. PhD is a plus.
• 8-10 years of professional experience in ML engineering, applied ML research, or a closely related role with significant production delivery.
• Deep expertise in Python and advanced proficiency with ML frameworks such as TensorFlow, PyTorch, or JAX.
• Extensive experience designing and operating production ML pipelines at scale.
• Strong knowledge of MLOps principles and tools including MLflow, Kubeflow, Airflow, Argo Workflows, or similar.
• Proven experience with cloud-native ML platforms (AWS SageMaker, Azure ML, GCP Vertex AI) and infrastructure-as-code practices.
• Experience with model serving at scale using frameworks such as TensorFlow Serving, Triton, BentoML, or Seldon.
• Strong understanding of distributed computing, data engineering, and scalable system design.
• Experience with monitoring, observability, and governance for production ML systems.
• Demonstrated ability to mentor engineers and influence technical direction.
• Excellent communication skills with the ability to present technical concepts to both technical and non-technical audiences.

Preferred Qualifications

• Experience with LLM-based systems, RAG pipelines, or agentic AI architectures.
• Experience with feature platforms (Feast, Tecton) and data quality frameworks (Great Expectations, Deequ).
• Familiarity with model explainability and fairness tools (SHAP, LIME, Fairlearn).
• Experience with real-time ML serving and streaming data pipelines (Kafka, Flink).
• Contributions to open-source ML/MLOps projects.
• Experience with GPU cluster management and cost optimization for training workloads.

Perks And Benefits Of Working With Us

• Unlimited PTO.
• Please ask us about our very generous parental leave, much above industry standards!.
• Entrepreneurial culture where pushing limits and taking risks is everyday business.
• Open communication with management and company leadership.
• Small, dynamic teams = massive impact.
• Medical, Dental and Vision coverage for employees.
• Access to Disability & Life insurance.
• Mental health and wellbeing support
• Annual bonus program
• Employer Stock Purchase Program (ESPP)
• Yearly Team building experiences
• Mentorship and sponsorship opportunities
• Manager resources and support

We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected characteristic.