We are looking for a highly skilled, technical, hands-on ML engineer with a solid background in building end-to-end AI/ML applications, exhibiting a strong aptitude for learning and keeping up with the latest advances in AI/ML. The candidate should also be proficient with AI literacy including Gen AI.
ResponsibilitiesThe ML Engineer is expected to develop AI/ML Engineering Solutions, perform DevOps and work closely with other stakeholders (ML Engineers, Data Scientists, and Data Engineers) with key responsibilities to:
- Develop ML Platform to empower Data Scientists to perform end to end ML Ops.
- Work actively and collaborate with Data Science teams within Credit IT to design and develop end to end Machine Learning systems.
- Lead evaluation of design options, tools, and utilities to build implementation patterns for MLOps using VertexAI in the most optimal ways.
- Create solutions and perform hands-on PoCs.
- Develop end to end and scalable Generative AI solutions.
- Work with Suppliers, Google Professional Services, and other Consultants as required.
- Collaborate with program managers to plan iterations, backlogs, and dependencies across all workstreams to progress the program at the required pace.
- Collaborate with Data/ML Engineering architects, SMEs, and technical leads to establish best practices for data products needed for model training and monitoring considering regulatory policy and legal compliance.
- Bachelor’s degree in computer science or related field.
- 8+ years of relevant work experience in solution, application, and ML engineering, DevOps with deep understanding of cloud hosting concepts and implementations.
- Proven expertise with Vertex AI.
- Very strong with programming in Python.
- Knowledge of SQL (Relational & Non-relational).
- 5+ years of hands-on experience in Analytics, MLOps and Engineering Solutions for ML based models.
- Knowledge of enterprise frameworks and technologies.
- Strong in engineering design patterns, experience with secure interoperability standards and methods, engineering tools and processes.
- Strong in containerization using Docker/Podman.
- Strong understanding on DevOps principles and practices, including continuous integration and deployment (CI/CD), automated testing & deployment pipelines.
- Good understanding of cloud security best practices and be familiar with different security tools and techniques like Identity and Access Management (IAM), Encryption, Network Security, etc.
- Understanding of microservices architecture.
- Strong leadership, communication, interpersonal, organizing, and problem-solving skills.
- Strong in AI Engineering
- The candidate needs to possess necessary Cloud experience (necessary) - preferably in GCP.
- Demonstrated industry experience in developing end to end production grade AI/ML systems in both Traditional ML and Generative AI.
- Proficiency in Agentic AI frameworks.
Preferred:
Relevant certification in ML Engineering in GCP (GCP - Professional Machine Learning Engineer certification)
Skills Required
- Bachelor's degree in computer science or related field
- 8+ years relevant experience in solution, application, and ML engineering, DevOps
- Proven expertise with Vertex AI
- Strong programming in Python
- Knowledge of SQL (relational and non-relational)
- 5+ years hands-on experience in Analytics, MLOps and engineering solutions for ML models
- Experience with enterprise frameworks and technologies
- Strong engineering design patterns and secure interoperability methods
- Containerization using Docker or Podman
- Strong understanding of DevOps principles and CI/CD, automated testing and deployment pipelines
- Understanding of cloud security best practices (IAM, encryption, network security)
- Understanding of microservices architecture
- Strong leadership, communication, interpersonal, organizing, and problem-solving skills
- Demonstrated experience building production-grade AI/ML systems in traditional ML and generative AI
- Proficiency in Agentic AI frameworks
- Necessary cloud experience (preferably GCP)
- Work with suppliers, Google Professional Services, and consultants as required
- Relevant certification in ML Engineering in GCP (Preferred)
Ford Motor Company Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Ford Motor Company and has not been reviewed or approved by Ford Motor Company.
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Healthcare Strength — Medical, dental, and vision coverage start on day one with options that include zero-premium plans, free mental health support, and wellness resources. For represented hourly employees, health plans are described as low-cost with strong coverage value.
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Retirement Support — A 401(k) with company match and additional company contributions is available from day one, alongside life and disability coverage. Pension eligibility in certain situations and financial-planning support reinforce long‑term security.
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Parental & Family Support — Paid parental leave, fertility, surrogacy, and adoption benefits, plus a ramp‑up program for returning parents, reflect a family‑focused package. Flexible Family Care days and generous time‑off options help address short‑term caregiving and personal needs.
Ford Motor Company Insights
What We Do
Ford is a global company with shared ideals and a deep sense of family. From our earliest days as a pioneer of modern transportation, we have sought to make the world a better place – one that benefits lives, communities and the planet. We are here to provide the means for every person to move and pursue their dreams, serving as a bridge between personal freedom and the future of mobility. In that pursuit, our 186,000 employees around the world help to set the pace of innovation every day.
