Location: Hybrid
Description:
We believe freedom of movement drives human progress. We also believe in providing you with the freedom to define and realize your dreams. With our incredible plans for the future of mobility, we have a wide variety of opportunities for you to accelerate your career potential as you help us define tomorrow's transportation.
We arelooking for a Machine Learning Engineer focused on building and driving the strategy forward for our internal Data Science / AI/ML platform. This role will work in a small, cross-functional team. The position will collaborate directly and continuously with other engineers, business partners, product managers and designers, and will release early and often. The team you will be working on is focused on buildingan AI/ML enablement platform to democratize Machine Learning across the enterprise (similar to Uber's Michelangelo, Facebook's FBLearner, etc).
Position Responsibilities
• Work closely with Tech Anchor, Product Manager and Product Owner to deliver MLOPs platform and Gen AI solution in GCP using Python and other tools for the data scientists and business across the company. • Work with software and ML engineers/Data Scientist to tackle challenging AIOps problems. • Maintain and mange current CI/CD ecosystem and tools • Find ways to automate and continually improve current CI/CD processes and release processes • Examine, inspect codes / scripts and resolve issues • Help innovate standardize machine learning development practices. • Experiment, innovate and share knowledge with the team. • Lead by example in use of Paired Programming for cross training/upskilling, problem solving, and speed to delivery. • Leverage latest ML/Gen AI / GCP/AIOPs/Kubernetes technologies
Experience Required:
• A Bachelor's degree in Computer Science / Computer Engineering or similar technical discipline.
• 2+ years of experience with Cloud Engineering / Services
• 3+ years of work experience as a backend software engineer in Python with exceptional software engineering knowledge.
• Experience with ML workflow orchestration tools: Airflow, Kubeflow etc.
• Advanced working knowledge of object-oriented/object function programming languages: Python, C/C++, Julia
• Experience in DevOps: Jenkins/Tekton etc.
• Experience with cloud services, preferably GCP Services like Vertex AI, Cloud Function, BigQuery etc.
• Experience in container management solution: Kubernetes, Docker
• Experience in scripting language: Bash, PowerShell etc.
• Experience with Infrastructure as code: Terraform etc
Experience Preferred:
• Experience and good understanding of GCP processing /DevOPs/ Machine Learning

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 [email protected] or 844-463-6178 .

Apex Systems is a world-class IT services company that serves thousands of clients across the globe. When you join 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.