Job description

MediaAlpha is a customer acquisition solutions provider powered by technology and data science. The company provides industry-leading solutions designed to reach consumers shopping within high-consideration categories such as property and casualty insurance, health insurance, life insurance, and more. Hybrid role: 3 days/week in office Role Overview As a Staff Machine Learning Engineer at MediaAlpha, you will lead the design and development of LLM-powered applications for our internal teams and ad serving platform. You will be accountable for end-to-end systems: owning strategy, architecture, implementation, and operations. You will collaborate with engineering, product, and business stakeholders to deliver intelligent systems that solve real business problems. The ideal candidate is a strong engineer with hands-on experience building LLM-powered applications in production, who works well across organizational boundaries and improves the conditions of any area they are in. We are an intentionally small organization, designed for agility, speed, and workability. Responsibilities Own the full software development lifecycle of LLM-powered systems, from requirements through production deployment and operational health. Design and implement retrieval-augmented generation (RAG) systems, tool-use patterns, and multi-step reasoning workflows. Integrate LLM-based services into MediaAlpha's products, internal tools, and data ecosystem. Drive architectural decisions balancing capability, cost, latency, and maintainability. Establish evaluation frameworks and metrics to measure application quality and business impact. Work directly with stakeholders to define product capabilities and develop new features and integrations. Be a champion of instilling excellence in coding, testing, and quality into the team and culture. Mentor engineers on LLM application development patterns and best practices. Requirements 9+ years of experience in software development. Experience designing and owning systems end-to-end, including 3-tier architectures, data flows, APIs, deployments, and operational health. Strong programming skills in Python, including software engineering methodologies and best practices. Hands-on experience building LLM-powered features in production. Experience with RAG architectures, including vector databases, embedding models, and retrieval strategies. Practical prompt engineering skills with demonstrated ability to iterate and evaluate quality. Familiarity with core ML concepts (classification, evaluation metrics, embeddings) and the judgment to know when traditional ML approaches outperform LLM-based solutions. Experience with agent frameworks and tool-use patterns (MCP, function calling, etc.). Familiarity with cloud environments (AWS preferred: EC2, S3, Bedrock). A self-starter who works independently, is comfortable with ambiguity, and pays careful attention to detail. Experience collaborating with engineers and non-technical stakeholders. Ability to articulate and communicate clearly, concisely, and thoughtfully. Organized and self-motivated. B.S. required, preferably in a technical discipline (e.g., computer science). Compensation & Benefits We are excited to offer a total base compensation of $170,000 to $260,000 per year for this position based on experience and qualifications. But that's not all - as a valued member of our team, you will also have access to an array of top-notch benefits, including: Annual bonus program and participation in our Restricted Stock Unit program 100% Employer-paid health, dental, and vision insurance for you, your dependents, and spouse or registered domestic partner 100% Employer paid long term disability, and life insurance 401(k) retirement plan with matching contributions to help you plan for your future Open Paid Time Off policy with a Birthday Hookie day off, 13 holidays, and 5 Recharge days Professional development reimbursement along with a subscription to LinkedIn Learning Cell Phone, Wellness, and Internet expense reimbursement, along with a subscription to the Calm App 100% fully paid parental leave for team members up to 22 weeks for the primary caregiver and 12 weeks for the secondary caregiver Dog-friendly offices (LA and AZ) along with a $300 pet adoption reimbursement Diversity, Equity, and Inclusion MediaAlpha is committed to fostering, cultivating, and maintaining a culture of diversity, equity, and inclusion. Our philosophy and actions are built on the premise that as an employer and citizens of our communities, we can create opportunities for lasting change. Fair Chance MediaAlpha will consider qualified applicants, including those with criminal histories, in a manner consistent with state and local "Fair Chance" laws. We are also committed to providing reasonable accommodations for qualified applicants with disabilities and disabled veterans in our application process. If you need assistance or an accommodation due to a disability, please contact us at peopleops@mediaalpha.com or (213) 316-6256.

Requirements

Must-haves

Own the full software development lifecycle of LLM-powered systems, from requirements through production deployment and operational health.
Design and implement retrieval-augmented generation (RAG) systems, tool-use patterns, and multi-step reasoning workflows.
Integrate LLM-based services into MediaAlpha's products, internal tools, and data ecosystem.
Drive architectural decisions balancing capability, cost, latency, and maintainability.
Establish evaluation frameworks and metrics to measure application quality and business impact.
Work directly with stakeholders to define product capabilities and develop new features and integrations.
Be a champion of instilling excellence in coding, testing, and quality into the team and culture.
Mentor engineers on LLM application development patterns and best practices.
9+ years of experience in software development.
Experience designing and owning systems end-to-end, including 3-tier architectures, data flows, APIs, deployments, and operational health.
Strong programming skills in Python, including software engineering methodologies and best practices.
Hands-on experience building LLM-powered features in production.
Experience with RAG architectures, including vector databases, embedding models, and retrieval strategies.
Practical prompt engineering skills with demonstrated ability to iterate and evaluate quality.
Familiarity with core ML concepts (classification, evaluation metrics, embeddings) and the judgment to know when traditional ML approaches outperform LLM-based solutions.
Experience with agent frameworks and tool-use patterns (MCP, function calling, etc.).
A self-starter who works independently, is comfortable with ambiguity, and pays careful attention to detail.
Experience collaborating with engineers and non-technical stakeholders.
Ability to articulate and communicate clearly, concisely, and thoughtfully.
Organized and self-motivated.
B.S. required, preferably in a technical discipline (e.g., computer science).
Compensation & Benefits

Nice-to-haves

Familiarity with cloud environments (AWS preferred: EC2, S3, Bedrock).
Annual bonus program and participation in our Restricted Stock Unit program

Application prep

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Keywords to mirror

machine learningllmpythonmlaws

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Health Insurance

Dental

Vision

401(K)

Paid Time Off

Parental Leave

Wellness

Professional Development