ML Ops Engineer (Contract to Hire)

Position: ML Ops Engineer
Location: Hybrid (Phoenix, AZ)
Duration: Long Term- Contract to Hire
About R Systems:
R Systems is a leading digital product engineering company that designs and develops chip-to-cloud software products, platforms, and digital experiences that empower its clients to achieve higher revenues and operational efficiency. Our product mindset and engineering capabilities in Cloud, Data, AI, and CX enable us to serve key players in the high-tech industry, including ISVs, SaaS, and Internet companies, as well as product companies in telecom, media, finance, manufacturing, and health verticals. We Are Great Place to Work Certified in 10 countries with a full-time workforce [India, USA, Canada, Poland, Romania, Moldova, Indonesia, Singapore, Malaysia & Thailand]! We are recognized as one of the Best Tech Brands 2024 by the Times Group and India's Top 500 Value Creators 2023 by Dun & Bradstreet.

Position Summary:
Client is building its first enterprise-scale MLOps platform on Snowflake. This role is a rare opportunity to design, build, operate, and continuously mature the end-to-end ML production ecosystem from scratch. The platform will be built on top of the enterprise medallion architecture (Bronze, Silver, Gold), and ML models will consume curated, governed data products from these layers to ensure quality, lineage, and scalability.
Job Details:
Architect and build a production-grade MLOps platform on Snowflake using Snowpark, Snowflake ML, Model Registry, and Feature Store capabilities.
Design and operationalize reusable ML pipelines for training, validation, deployment, inference, and monitoring.
Build MLOps workflows aligned to Bronze, Silver, and Gold layers so model training and inference consistently consume trusted medallion data.
Establish model lifecycle management standards, including versioning, approval workflows, promotion gates, rollback strategy, and model lineage.
Partner with data scientists to productionize models quickly and safely, transforming experiments into reliable, scalable services.
Implement model observability for performance, drift, bias, data quality, and service reliability with actionable alerting and SLOs.
Automate retraining and refresh workflows using Snowflake Tasks, Dynamic Tables, and event-driven orchestration patterns.
Partner with data engineering to ensure feature pipelines are reliable, reusable, and synchronized with medallion layer evolution.
Define and implement CI/CD for ML workflows (code, data, models, and configuration), including testing frameworks and release controls.
Drive MLOps governance across security, compliance, auditability, reproducibility, and responsible AI practices.
Lead platform maturation from MVP to enterprise scale, including documentation, developer enablement, and operational runbooks.
Required Qualifications:
5+ years of experience in ML Engineering, MLOps, or related platform engineering roles.
Strong Python and SQL expertise, with proven experience building production ML pipelines.
Hands-on experience with Snowflake data and compute patterns; experience with Snowpark and Snowflake-native ML tooling strongly preferred.
Demonstrated experience with model deployment, versioning, monitoring, and lifecycle governance in production.
Experience implementing CI/CD and testing strategies for ML systems.
Solid understanding of feature engineering pipelines, training-serving consistency, and data quality controls.
Experience with cloud infrastructure and services (AWS preferred).
Strong collaboration skills and ability to work cross-functionally with data science, data engineering, and business stakeholders.
Preferred Qualifications:
Experience with Snowflake Model Registry, Snowflake Feature Store, and model observability within Snowflake.
Experience designing ML systems on medallion/lakehouse-style data architectures.
Experience with dbt or similar transformation frameworks.
Familiarity with streaming or near-real-time inference patterns.
Experience in high-volume operational domains such as logistics, fleet, route optimization, or environmental services.
Prior experience building greenfield platforms and defining operating standards from the ground up.


Why Join R Systems?

• Frequent Internal Hackathons: Engage in dynamic competitions with exciting prizes to keep your skills sharp.
• Cultural Celebrations: Strengthen our familial bonds through shared celebrations, fostering a sense of community.
• Diverse Project Exposure: Work on a variety of projects across sectors like Healthcare, Banking, e-commerce, and Retail, collaborating with leading global brands.
• Centre of Excellence (COE): Benefit from technical guidance and upskilling opportunities provided by our team of technology experts, helping you navigate your career path.
• E-Learning Platform: Gain access to comprehensive e-learning platforms coupled with a robust mentorship program to enhance your skills.
• Open Door Policy: Embrace a culture of mutual support, respect, and open dialogue, promoting a collaborative work environment.

If you are passionate and excited about working in a fast-paced, innovative environment, we would love to hear from you!

R Systems is an equal opportunity employer that does not discriminate against any employee or job applicant because of race, color, religion, national origin, sex, physical or mental disability, age, or any other characteristic protected by law. We strive to build a team that reflects the diverse communities we serve, and we actively encourage applications from individuals of all backgrounds and experiences. Our commitment to equal opportunity extends to all aspects of employment, including recruitment, hiring, training, promotion, and benefits.
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