Apply advanced data science, machine learning, and Generative AI techniques to solve complex business problems and enable AI-powered capabilities across the enterprise.
Compensation
Base Pay Range
$85,000.00 - $150,000.00
Responsibilities
Analyze large and complex datasets using statistical, machine learning, and advanced analytical techniques to identify patterns, generate insights, and solve business problems.
Design, develop, evaluate, and optimize machine learning models using appropriate statistical and ML methodologies, including feature engineering, model validation, performance testing, and ongoing monitoring.
Develop and evaluate Generative AI solutions using foundation models, including prompt engineering, retrieval-augmented generation (RAG), embeddings, semantic search, and agentic AI techniques where appropriate.
Develop rigorous evaluation frameworks and experimentation approaches to measure model quality, accuracy, relevance, safety, and business impact.
Acquire, cleanse, transform, and integrate structured and unstructured data from multiple sources to support analytical modeling and AI solutions.
Requirements
Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or equivalent
Nice to have: Master's degree in relevant quantitative discipline
Lead technical design and delivery of Freddie Mac’s internal GenAI platform, FredAI, ensuring secure, scalable, and responsible AI solutions across the enterprise.
Compensation
This position has an annualized market-based salary range of $149,000 - $223,000 and is eligible to participate in the annual incentive program.
Responsibilities
Provide hands‑on technical leadership for architecture, design, and delivery of FredAI capabilities
Design and implement reusable reference architectures, SDKs, shared services, APIs, and integration patterns
Implement rigorous evaluation, testing, and LLMOps practices
Engineer secure, permission‑aware solutions enforcing identity, entitlements, data boundaries, privacy, and responsible AI policies
Define model and platform integration patterns, including routing, caching, rate limiting, and cost management
Requirements
Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical field
We are seeking an AI & Machine Learning Manager with strong hands‑on expertise in AI/ML engineering, Generative AI, data science and enterprise solution delivery.
Responsibilities
Work with business leaders and domain teams to identify, assess and prioritise AI/ML opportunities based on business value, feasibility, risk and expected return.
Translate business problems into clear AI use cases, functional requirements, solution options, delivery plans and measurable success criteria.
Define AI roadmaps and support business cases, proof‑of‑concept assessments and the transition of successful pilots into production solutions.
Lead the design, development, testing and deployment of machine learning, deep learning, NLP, predictive analytics and Generative AI solutions.
Guide the development of LLM‑based applications, Retrieval‑Augmented Generation (RAG), AI agents, conversational systems and intelligent automation solutions.
Requirements
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering or a related discipline
Lead the design, development, and operation of AI applications for Supply Chain and enterprise Digital. A senior individual contributor role combining hands-on engineering, architecture, technical leadership, and mentoring.
Compensation
The salary range for this role is $145,900.00 - $234,200.00.
Responsibilities
Design and build full-stack AI applications, including user interfaces, backend APIs, reusable services, and integrations with enterprise data and systems.
Own delivery from prototype through production, including automated testing, CI/CD, release management, observability, incident response, and ongoing application support.
Use AI coding agents for implementation, refactoring, debugging, and test generation.
Partner with product, architecture, cybersecurity, quality, and validation teams to meet business outcomes, enterprise standards, and applicable regulatory requirements.
Seeking an applied workforce scientist who combines advanced quantitative methods, employee listening analytics expertise, and business judgment to reveal how employees experience the organization and what most influences engagement, culture, retention, and organizational health.
Compensation
Base Pay Range for this position $122,100 - $162,800
Responsibilities
Build and validate statistical and machine learning models (regression, classification, survival analysis, clustering, key-driver analysis) to explain and predict engagement, retention, culture, and organizational health outcomes.
Design rigorous analyses, including quasi-experimental and causal inference approaches, to assess the impact of programs, leader actions, and listening interventions.
Apply survey science and psychometrics, including sampling, weighting, reliability, validity, and measurement invariance, to maintain the credibility of listening data.
Conduct open-ended discovery to test hypotheses, explore anomalies, and identify previously unseen relationships.
Use Python or R and SQL to integrate, transform, and analyze survey, lifecycle, HRIS, operational, and business data at enterprise scale.
Requirements
Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Economics, Industrial-Organizational Psychology with a quantitative focus, or a related field
Master's degree or PhD preferred
Senior Software Engineer - AI Tooling & Quality Engineering Platforms
Design and build advanced AI‑powered tooling and internal platforms that modernize quality engineering across the organization. Building production systems, internal platforms, and intelligent automation services.
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