AI/ML Engineer

Ford • Dearborn, MI

5d • Hybrid

About The Position

We are the movers of the world and the makers of the future. We get up every day, roll up our sleeves and build a better world -- together. At Ford, we're all a part of something bigger than ourselves. Are you ready to change the way the world moves? The Ford Motor Credit Company team helps put people behind the wheels of great Ford and Lincoln vehicles. By partnering with dealerships, we provide financing, personalized service and professional expertise to thousands of dealers and millions of customers in over one hundred countries around the world. In this position... As a Senior AI/ML Engineer at Credit AI, you will be responsible for designing, building, and operationalizing scalable AI systems and intelligent agents to enhance customer outcomes, mitigate financial risk, and boost operational efficiency at Ford Credit. This hands-on role involves leading end-to-end strategic AI initiatives, from conversational agents to fraud detection and business automation, while balancing rapid experimentation with production rigor and ensuring compliance with financial regulatory requirements.

Requirements

• Bachelors degree
• 3+ years of applied ML/AI experience with at least 1 years focused on production ML systems and engineering.
• Strong software engineering skills: advanced Python, modular design, testing, typed codebases and deployment experience.
• Production ML/MLOps experience: containerization (Docker), orchestration (Kubernetes), CI/CD tooling, infra-as-code (Terraform/CloudFormation), and deployment frameworks (TFX, MLflow, KServe/Seldon/BentoML or equivalent).

Nice To Haves

• Practical experience with modern ML frameworks: scikit-learn, PyTorch or TensorFlow.
• Hands-on experience designing, building, and productionizing AI agents using modern frameworks (e.g., LangChain, Google ADK, LlamaIndex or similar), including RAG/embedding pipelines, memory/state management, tool-using agent patterns, vector DB integration, secure connector design, and operational guardrails for safe human-in-the-loop orchestration.
• Experience designing or productionizing agent architectures: tool-using agents, planner/actor patterns, memory/state management, and safe orchestration of multi-step tasks.
• Strong data engineering skills: SQL, data modeling, experience with big data platforms (Spark, Databricks, Snowflake, BigQuery or similar) and streaming/event-driven systems.
• Demonstrated ability to design and implement model and agent monitoring, data quality checks, drift detection and alerting.
• Knowledge of model explainability and fairness tooling (SHAP, LIME, integrated gradients or equivalent) and experiment design / A/B testing methodologies.
• Experience working in regulated environments (credit/finance preferred) and producing artifacts for model risk, audit, and compliance.
• Strong verbal and written communication skills with experience distilling complex technical topics for non-technical stakeholders.

Responsibilities

• Lead architecture, design, and implementation of production-grade ML/AI systems, data pipelines, and intelligent agents to meet business and regulatory objectives across credit products.
• Translate business problems into engineering solutions: define success metrics, SLAs, evaluation protocols, and experimentation plans focused on measurable business impact.
• Design, prototype, validate, and productionize AI agents (conversational agents, task-execution agents, and orchestration workflows) that safely automate business processes, augment agent workflows, and integrate with backend systems.
• Own full model and agent lifecycle: data ingestion and lineage, feature engineering, model and policy development, agent orchestration, deployment, monitoring, and automated retraining.
• Collaborate to build and maintain robust MLOps and agent-ops practices: containerized agent runtimes, CI/CD for models and agent components, infra-as-code, canary/blue-green releases, and safe rollout strategies.
• Implement monitoring and observability for models and agents (performance, task success, hallucination/safety metrics, drift, data quality, latency); create incident playbooks and operationalize retraining, rollbacks, and human handoff procedures.
• Design and run rigorous evaluation frameworks for agents: scenario-based testing, simulation, backtests, holdouts, cross-validation, A/B and uplift testing, and business-impact estimation.
• Drive responsible AI: implement explainability, fairness assessments, access controls, data minimization, privacy safeguards, and mitigation plans for bias, safety or other harms from agent outputs.
• Architect guardrails for autonomous agents (authorization, scope-limiting, confirmation flows, human-in-the-loop escalation, sandboxing, and cost controls).
• Lead cross-functional stakeholder communication: present technical trade-offs, agent capabilities and limitations, risk assessments and outcomes to product owners, legal, risk/compliance and senior leadership.
• Continuously evaluate and recommend improvements to AI safety guardrails, agent orchestration tooling and the SDLC to accelerate delivery while maintaining safety/compliance.

Benefits

• Immediate medical, dental, vision and prescription drug coverage
• Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more
• Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more
• Vehicle discount program for employees and family members and management leases
• Tuition assistance
• Established and active employee resource groups
• Paid time off for individual and team community service
• A generous schedule of paid holidays, including the week between Christmas and New Year's Day
• Paid time off and the option to purchase additional vacation time

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees