ML Ops Engineer

Job#: 3034035

Job Description:

Role: ML Ops Engineer

Duration: Long-Term Contract

Location: Hybrid - 4 days/week onsite

Description:

This role focuses on building and scaling enterprise-grade ML Ops and data engineering solutions to support connected vehicle data and agentic AI initiatives. The individual will design, implement, and optimize data pipelines and machine learning operations in a cloud-native environment, ensuring performance, reliability, and governance at scale.

Key Responsibilities

ML Ops & Machine Learning

• Build scalable, secure, and high-performance ML data pipelines in the cloud to process large volumes of connected vehicle data
• Support and evolve ML/AI solutions, including agentic systems, with a focus on performance optimization, cost efficiency, and security
• Implement continuous learning frameworks to improve model accuracy and performance over time

Data Engineering & Platform Development

• Design and develop data products leveraging both streaming and batch ingestion patterns on Google Cloud Platform
• Build and maintain data pipelines to monitor:
  • Data quality
  • Model performance
  • Agentic solution effectiveness
• Support real-time and large-scale data processing using modern data engineering practices

DevOps & Platform Operations

• Manage and maintain data platform infrastructure using Terraform and CI/CD pipelines
• Enhance DevOps capabilities, including continuous integration, deployment, and automation
• Monitor production pipelines and provide support in accordance with SLAs
• Identify and resolve code quality and security issues using tools such as SonarQube, Checkmarx, Fossa, and Cycode

Data Governance & Quality

• Implement and promote enterprise data governance practices, including:
  • Data protection
  • Standardization
  • Quality and reuse
• Perform data mapping, lineage tracking, and documentation of data flows
• Provide visibility into data quality, vehicle, and feature-level issues and partner with stakeholders to resolve

Collaboration & Continuous Improvement

• Collaborate with cross-functional teams to streamline data acquisition, processing, and analytics delivery
• Support business and product teams with insights derived from connected vehicle data
• Stay current with emerging data engineering and ML Ops practices and contribute to the technical direction of the organization
• Mentor junior team members and promote best practices across the team

Required Skills

• Strong communication skills with the ability to translate complex ML/AI concepts to both technical and non-technical audiences
• Deep expertise in Google Cloud Platform (Google Cloud Platform)
• Strong experience in ML Ops, Machine Learning, and AI systems
• Proficiency in Python and familiarity with Java, Spark, and SQL
• Experience building scalable data pipelines and microservices architectures
• Knowledge of:
  • Apache Kafka or real-time streaming platforms
  • REST APIs for system integration
  • DevOps tooling (GitHub, Tekton, Docker, Terraform, CI/CD pipelines)
• Experience implementing data governance frameworks

Preferred Skills

• Experience with connected vehicle data or telematics
• Data modeling and database design expertise
• Experience with cloud infrastructure and distributed systems
• Data mining and advanced analytics experience
• Strong troubleshooting and problem-solving skills
• Experience mentoring or supporting junior team members

Required Experience

• Bachelor's degree in Computer Science, Software Engineering, Data Engineering, or related field, plus 6+ years of experience (or equivalent combination)
• 4+ years of experience in:
  • Data engineering and data product development
  • Software development and production system delivery
• Experience with at least three of the following:
  • Java, Python, Spark, Scala, SQL
• 3+ years of experience building scalable cloud-based data pipelines using:
  • Data warehousing solutions (e.g., BigQuery, Redshift, Synapse)
  • Workflow orchestration tools (e.g., Airflow)
  • Relational databases (MySQL, PostgreSQL, SQL Server)
  • Streaming platforms (Kafka, Pub/Sub)
  • Microservices architectures and REST APIs
  • DevOps tools (GitHub, Tekton, Terraform, Docker)
  • Agile tools (Jira)

Preferred Experience

• Master's or PhD in a related field
• Hands-on experience with ML model development and/or ML Ops
• Experience contributing to open-source projects
• Experience with cloud architecture design and migrations
• Google Cloud Platform certifications
• Proven ability to:
  • Automate complex data pipelines
  • Troubleshoot and optimize data platforms
  • Communicate complex technical concepts clearly
  • Deliver end-to-end solutions from design to production

Education

• Required: Bachelor's Degree
• Preferred: Master's Degree or higher

EEO Employer

Apex Systems is an equal opportunity employer. We do not discriminate or allow discrimination on the basis of race, color, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), age, sexual orientation, gender identity, national origin, ancestry, citizenship, genetic information, registered domestic partner status, marital status, disability, status as a crime victim, protected veteran status, political affiliation, union membership, or any other characteristic protected by law. Apex will consider qualified applicants with criminal histories in a manner consistent with the requirements of applicable law. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation in using our website for a search or application, please contact our Employee Services Department at or .

Everforth Apex is a world-class IT services company that serves thousands of clients across the globe. When you join Everforth Apex, you become part of a team that values innovation, collaboration, and continuous learning. We offer quality career resources, training, certifications, development opportunities, and a comprehensive benefits package. Our commitment to excellence is reflected in many awards, including ClearlyRated's Best of Staffing in Talent Satisfaction in the United States and Great Place to Work in the United Kingdom and Mexico. Everforth Apex uses a virtual recruiter as part of the application process. Click for more details.

Everforth Apex Benefits Overview: Everforth Apex offers a range of supplemental benefits, including medical, dental, vision, life, disability, and other insurance plans that offer an optional layer of financial protection. We offer an ESPP (employee stock purchase program) and a 401K program which allows you to contribute typically within 30 days of starting, with a company match after 12 months of tenure. Everforth Apex also offers a HSA (Health Savings Account on the HDHP plan), a SupportLinc Employee Assistance Program (EAP) with up to 8 free counseling sessions, a corporate discount savings program and other discounts. In terms of professional development, Everforth Apex hosts an on-demand training program, provides access to certification prep and a library of technical and leadership courses/books/seminars once you have 6+ months of tenure, and certification discounts and other perks to associations that include CompTIA and IIBA. Everforth Apex has a dedicated customer service team for our Consultants that can address questions around benefits and other resources, as well as a certified Career Coach. You can access a full list of our benefits, programs, support teams and resources within our 'Welcome Packet' as well, which an Everforth Apex team member can provide.