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video production specialist

Affirm

<div>
 Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest.
 
 
 On the Servicing ML team, you will build and improve machine learning and AI systems that automate customer operations such as disputes, returns, fraud, and chargebacks to make the best decisions for Affirm and our customers. You will work closely with experienced ML engineers, platform partners, and cross-functional stakeholders to take models from idea to prototype to production, and to keep them healthy with strong measurement and monitoring.
 
 
 
 What You'll Do
 
 
 
 <ul>
 <li>
 You will develop AI systems that automate dispute and chargeback handling using structured evidence and business logic, creating a better experience for our customers.
 </li>
 <li>
 You will build models that automate refunds, getting money back to our customers faster.
 </li>
 <li>
 You will build and maintain evidence extraction pipelines that process unstructured data using LLM-powered workflows to produce structured, actionable outputs.
 </li>
 <li>
 You will prototype new modeling ideas, run offline experiments, and drive the best-performing approaches into production with appropriate risk controls.
 </li>
 <li>
 You will collaborate across Engineering, Servicing Operations, Product, and ML Platform to define requirements, evaluate tradeoffs, and communicate results clearly to both technical and non-technical audiences.
 
 
 </li>
 </ul>
 
 What We Look For
 
 
 
 <ul>
 <li>
 You have a total of 2+ years of experience as a machine learning engineer
 </li>
 <li>
 Strong Python skills and experience writing production-quality code
 </li>
 <li>
 Experience building and evaluating models for tabular classification problems (preferably gradient-boosted decision trees like LightGBM/XGBoost/CatBoost).
 </li>
 <li>
 Experience building applications with LLM APIs (e.g., OpenAI, Anthropic), including structured extraction, prompt engineering, and orchestration frameworks like LangChain or LangGraph.
 </li>
 <li>
 Familiarity with document and unstructured data processing (PDF/image extraction, text parsing, or similar).
 </li>
 <li>
 Experience with ML lifecycle tooling for training orchestration, experimentation, and model monitoring (e.g., Kubeflow, Airflow, MLflow, or equivalent internal platforms).
 </li>
 <li>
 Proficient in using AI-powered developer tools (e.g., Claude Code, Cursor, or similar) to accelerate iteration, debugging, and code quality as part of day-to-day development workflows.
 </li>
 <li>
 You have mastered taking a simple problem or business scenario into a solution that interacts with multiple software components, and executing on it by writing clear, easily understood, well tested and extensible code.
 </li>
 <li>
 You are comfortable navigating a large code base, debugging others' code, and providing feedback to other engineers through code reviews.
 </li>
 <li>
 Your experience demonstrates that you take ownership of your growth, proactively seeking feedback from your team, your manager, and your stakeholders.
 </li>
 <li>
 You have strong verbal and written communication skills that support effective collaboration with our global engineering team.
 </li>
 <li>
 This position requires either equivalent practical experience or a Bachelor&rsquo;s degree in a related field
 
 
 </li>
 </ul>
 
 Base Pay Grade
 
 - L
 
 
 
 Equity Grade
 
 - 6
 
 
 Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills.
 
 
 Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents.)
 
 
 USA base pay range (CA, WA, NY, NJ, CT) per year: $165,000 - $225,000
 
 
 USA base pay range (all other U.S. states) per year: $146,000 - $206,000
 
 
 Affirm is proud to be a remote-first company! The majority of our roles are remote and you can work almost anywhere within the country of employment. Affirmers in proximal roles have the flexibility to work remotely, but will occasionally be required to work out of their assigned Affirm office. A limited number of roles remain office-based due to the nature of their job responsibilities.
 
 
 
 Benefits
 
 
 
 We&rsquo;re extremely proud to offer competitive benefits that are anchored to our core value of people come first. Some key highlights of our benefits package include:
 
 
 <ul>
 <li>
 Health care coverage - Affirm covers all premiums for all levels of coverage for you and your dependents
 </li>
 <li>
 Flexible Spending Wallets - generous stipends for spending on Technology, Food, various Lifestyle needs, and family forming expenses
 </li>
 <li>
 Time off - competitive vacation and holiday schedules allowing you to take time off to rest and recharge
 </li>
 <li>
 ESPP - An employee stock purchase plan enabling you to buy shares of Affirm at a discount
 
 
 </li>
 </ul>
 We believe It&rsquo;s On Us to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process.
 
 
 [For U.S. positions that could be performed in Los Angeles or San Francisco] Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles Fair Chance Initiative for Hiring Ordinance, Affirm will consider for employment qualified applicants with arrest and conviction records.
 
 
 By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and hereby freely and unambiguously give informed consent to the collection, processing, use, and storage of your personal information as described therein.
 
 
</div>

Machine Learning Engineer II (Servicing ML)

Humana

<div>
 
 Become a part of our caring community
 
 
 
 The Lead Software Engineer codes software applications based on business requirements. The Lead Software Engineer works on problems of diverse scope and complexity ranging from moderate to substantial.
 
 
 The Lead Software Engineer standardizes the quality assurance procedure for software. Oversees testing and debugging and develops fixes. Researches complaints and makes necessary adjustments and/or recommendations to resolve complex software related issues. Advises executives to develop functional strategies (often segment specific) on matters of significance. Exercises independent judgment and decision making on complex issues regarding job duties and related tasks, and works under minimal supervision, Uses independent judgment requiring analysis of variable factors and determining the best course of action.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Technical Architecture and Ownership:** Design and own the end-to-end architecture of Centerwell's AI systems, including LLM-powered clinical tools, RAG pipelines, harnesses, agent-based workflows, and intelligent automation. Make and communicate foundational technical decisions in close collaboration with the broader engineering team.
 </li>
 <li>
 Model Development and Fine-Tuning:** Evaluate, select, and where appropriate guide the fine-tuning of foundation models. Establish model evaluation frameworks that prioritize safety, accuracy, and clinical relevance.
 </li>
 <li>
 Clinical and Product Partnership:** Collaborate closely with product managers, designers, clinicians, and data stakeholders to understand care delivery workflows and translate them into well-scoped, high-impact AI features.
 </li>
 <li>
 HIPAA Compliance and Responsible AI:** Ensure all AI systems are designed, deployed, and monitored in compliance with HIPAA and Humana's Responsible AI standards, including participation in AIRB and Responsible AI Council review processes where applicable.
 
 
 </li>
 </ul>
 
 Required Qualifications
 
 
 
 
 Use your skills to make an impact
 
 
 
 <ul>
 <li>
 B.S. or M.S. in Computer Science, Engineering, or a related field (or equivalent experience)
 </li>
 <li>
 8+ years of software engineering experience, with 4+ years focused on production AI/ML systems
 </li>
 <li>
 Deep, hands-on experience building with large language models and orchestration frameworks (LangChain, LlamaIndex, or equivalent)
 </li>
 <li>
 Strong proficiency in Python, Typescript and modern ML tooling (Hugging Face, PyTorch, or similar)
 </li>
 <li>
 Proven experience designing and deploying RAG pipelines and vector search systems in production
 </li>
 <li>
 Working knowledge of model fine-tuning approaches (LoRA, RLHF, instruction tuning, or equivalent)
 </li>
 <li>
 Experience designing and implementing custom LLM and agent evaluation frameworks, including automated eval pipelines, benchmark construction, and output quality assessment at scale
 </li>
 <li>
 Experience designing and building multi-agent AI systems, including agent orchestration, tool use, and sandboxed execution environments
 </li>
 <li>
 Demonstrated ownership of complex AI systems end-to-end, from architecture through production operation
 </li>
 <li>
 Understanding of HIPAA requirements and secure handling of protected health information (PHI)
 </li>
 <li>
 Strong written and verbal communication skills across technical and non-technical audiences
 </li>
 <li>
 Hands-on experience with AI-assisted development tools and LLM coding harnesses (Claude Code, Pi Agent, Cursor, Codex, or similar)
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience in healthcare, clinical informatics, or other highly regulated industries
 </li>
 <li>
 Exposure to clinical NLP, medical coding, or EHR/FHIR data standards
 </li>
 <li>
 Experience operating AI systems at scale on cloud platforms (AWS, Azure, or GCP)
 
 
 </li>
 </ul>
 A
 
 dditional Information
 
 
 
 
 The candidate must live close to one of our designated IT locations: NYC, NY; Louisville, KY; Tampa, FL; Fort Lauderdale, FL; Dallas/Frisco, TX; Boston, MA; Washington, D.C: Atlanta, GA, Nashville, TN, Chicago, IL, or Charlotte, NC.
 
 
 
 
 Scheduled Weekly Hours
 
 
 
 40
 
 
 
 Pay Range
 
 
 
 The compensation range below reflects a good faith estimate of starting base pay for full time (40 hours per week) employment at the time of posting. The pay range may be higher or lower based on geographic location and individual pay will vary based on demonstrated job related skills, knowledge, experience, education, certifications, etc.
 
 
 $129,300 - $177,800 per year
 
 
 This job is eligible for a bonus incentive plan. This incentive opportunity is based upon company and/or individual performance.
 
 
 
 Description Of Benefits
 
 
 
 Humana, Inc. and its affiliated subsidiaries (collectively, &ldquo;Humana&rdquo;) offers competitive benefits that support whole-person well-being. Associate benefits are designed to encourage personal wellness and smart healthcare decisions for you and your family while also knowing your life extends outside of work. Among our benefits, Humana provides medical, dental and vision benefits, 401(k) retirement savings plan, time off (including paid time off, company and personal holidays, paid parental and caregiver leave), short-term and long-term disability, life insurance and many other opportunities.
 
 
 
 About Us
 
 
 
 About Humana: Humana Inc. (NYSE: HUM) is a leading U.S. healthcare company. Through our Humana insurance services and our CenterWell healthcare services, we make it easier for the millions of people we serve to achieve their best health &ndash; delivering the care and service they need, when they need it. These efforts are leading to a better quality of life for people with Medicare and Medicaid, families, individuals, military service personnel, and communities at large. Learn more about what we offer at Humana.com and at CenterWell.com.
 
 
 
 Equal Opportunity Employer
 
 
 
 It is the policy of Humana not to discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability or protected veteran status. It is also the policy of Humana to take affirmative action, in compliance with Section 503 of the Rehabilitation Act and VEVRAA, to employ and to advance in employment individuals with disability or protected veteran status, and to base all employment decisions only on valid job requirements. This policy shall apply to all employment actions, including but not limited to recruitment, hiring, upgrading, promotion, transfer, demotion, layoff, recall, termination, rates of pay or other forms of compensation and selection for training, including apprenticeship, at all levels of employment.
</div>

Lead Software Engineer - AI

GE Aerospace

<div><h1 class="jobSectionHeader">Job Description Summary</h1>
At GE Aerospace, our AI engineers don&rsquo;t just support projects &mdash; they help drive them. From day one, interns and co-ops take on real-world challenges, owning work from start to finish and building solutions that connect data, tools, cloud, AI, and engineering to advance the future of flight. 
 
As an intern, you'll build expertise in cloud platforms, databases, data engineering, web design, Al technologies, and numerical methods to solve real-world engineering problems. Through hands-on projects, you'll work with the Innovator Method, Game Theory, and DecisionIQ, turning customer insights into impactful solutions. You'll have the opportunity to learn, contribute, and bring real business value and help shape the future of aerospace design.<h1 class="jobSectionHeader">
Job Description</h1>
What You will Do<ul><li>
Develop technical solutions for engineers to evaluate and adopt data and AI solutions.</li><li>
Consult on architecture, implement proof of concepts and deliver solutions for business strategic projects, including data science and machine learning systems.</li><li>
Build and present product architectures, write technical code, and demo applications to stakeholders.</li><li>
Gain hands-on experience with the Innovator Method, Game Theory, and DecisionIQ and turn customer insights into solution that deliver real business value.</li><li>
Sharpen your skills in cloud platforms, databases, data engineering, web design, AI technologies, and numerical methods.</li><li>
Use your strengths to support team members and build cross-functional relationships across the company.</li><li>
Work to ship solutions to production that meet business needs and drive impact.</li></ul>
Our culture thrives on innovation, diversity, and deep collaboration. You&rsquo;ll contribute as both a learner and a builder, helping us push the design frontier in aerospace.
Qualifications<ul><li>
Currently enrolled in a Bachelor&rsquo;s degree program in Computer Science, Aerospace Engineering, Mechanical Engineering; or a related field at an accredited university or credentialed software accelerator program.</li><li>
Minimum 3.7 cumulative GPA off a 4.0 scale without rounding</li></ul>
No prior work experience is required.
Desired Characteristics<ul><li>
Strong academic performance in Computer Science or other STEM disciplines</li><li>
Experience designing AI solutions and architecting distributed data systems</li><li>
Proficiency in programming and debugging with Python, C#, C++, and SQL</li><li>
Customer-centric mindset with ability to lead design thinking workshops</li><li>
Hands-on experience in at least one of the following areas: Machine Learning, Large Language Models (LLMs), or Computer Vision</li><li>
Experience building solutions using public cloud platforms such as AWS or Azure</li><li>
AWS and/or Azure certification</li></ul>
About The Internship<ul><li>
Location: Remote</li><li>
Pay rates for this position begin at $20/hour and increase for each undergraduate year completed. Relocation support and housing assistance is available for those who relocate to a new city.</li><li>
Travel Opportunities</li><li>
Real-world project ownership</li><li>
Mentorship from experienced engineers</li><li>
Opportunity for return offers</li></ul>
Equal Opportunity Employer
GE Aerospace offers a great work environment, professional development, challenging careers, and competitive compensation. GE Aerospace is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.
#LI-Remote - This is a remote position<h1 class="jobSectionHeader">
Additional Information</h1><div><div><div><div><div><div><div>
GE Aerospace offers a great work environment, professional development, challenging careers, and competitive compensation. GE Aerospace is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.</div></div></div></div></div></div></div>
GE Aerospace will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable). Employees may also be subject to random and reasonable-suspicion drug and alcohol testing.<div><div><div><div><div><div><div> 
Relocation Assistance Provided: No</div></div></div></div></div></div></div>
#LI-Remote - This is a remote position</div>

Applied AI Engineer Intern – Summer 2027 (May/June Start)

Ditto

<div>
 
 About Ditto
 
 
 
 Ditto is redefining how data moves at the edge. Our mission is to make it seamless for developers to build resilient, real-time applications, regardless of network conditions. Whether you're in a stadium, airplane, or remote military base, Ditto's peer-to-peer sync engine ensures devices stay connected and data stays consistent, even without internet. With more than $145 million in funding and trusted by organizations like Chick-fil-A, Delta Airlines, and the U.S. military, Ditto powers mission-critical experiences across aviation, retail, travel, hospitality, defense, and more. As a globally distributed, fast-growing startup, we&rsquo;re committed to building a diverse and inclusive team that reflects the wide range of perspectives needed to solve the world&rsquo;s hardest connectivity problems.
 
 
 As an AI Engineer at Ditto, you build the system that builds our software. We are moving engineering from handcraft &mdash; every change written, tested, and shipped by a person tending it one at a time &mdash; to an operated platform where agents do the work and engineers tend the agents. You will help build Symphony: the brief runtime that executes agent teams, the typed tool surface those agents reach the host through, the telemetry that makes every run measurable, and the evaluation loop that turns a bad output into a better brief instead of a hand-patched diff.
 
 
 This is deliberately a blend of AI engineering and developer tooling, because at this layer they are the same job. Getting an agent to reliably build, test, and ship an iOS change is part prompt and context design, part sandboxing and process supervision, part CI and release plumbing, and entirely a measurement problem. Your users are Ditto's own engineers, and your product is the thing they run every day &mdash; so you will care as much about a clear error message and a fast local loop as you do about token cost per completed task. This role suits someone comfortable in ambiguity, opinionated about evaluation over intuition, and happy to own a system end to end.
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Build the agent execution runtime: Design and ship the layer that compiles a brief into a running team of agents &mdash; topology and handoffs, deterministic gates, the shared message bus, session lifecycle, and the recovery behavior that keeps a long run from losing its work.
 </li>
 <li>
 Design the tool surface agents work through: Replace "here is a shell, please be careful" with typed, versioned toolpacks backed by reviewed repository recipes &mdash; sandboxed execution boundaries, lease handling, process-tree ownership, and MCP servers that expose our internal systems to agents safely.
 </li>
 <li>
 Make quality measurable, then improve it: Build the evals, benchmarks, and metric sets that score a run; instrument the system with per-phase timing, structured error taxonomies, and cost attribution; and use that signal to tune prompts, context, and topology rather than guessing.
 </li>
 <li>
 Own the model substrate as a swappable input: Bind briefs to capability classes instead of vendor model names, work with routing and inference infrastructure across hosted and on-prem serving, and tune context, caching, and model selection against real cost, latency, and accuracy data.
 </li>
 <li>
 Partner with service teams and raise the bar: Work directly with Ditto's engineering teams to turn their workflows into briefs they trust, establish the patterns others compose from, and mentor engineers as agentic development becomes the default path rather than the experiment.
 
 
 </li>
 </ul>
 What You'll Need
 
 
 <ul>
 <li>
 5+ years of professional software engineering experience, including meaningful time building and operating LLM-backed systems in production &mdash; not prototypes or demos, but something real people depended on.
 </li>
 <li>
 Hands-on depth with agentic systems: tool and function calling, multi-agent orchestration, context and prompt engineering, structured output, and a practical understanding of where these systems fail and why.
 </li>
 <li>
 Strong developer-tooling instincts from building the things engineers depend on &mdash; CLIs, build systems, CI/CD, internal platforms &mdash; with the empathy for the daily loop that comes from having been the person on call for it.
 </li>
 <li>
 A rigorous approach to evaluation. You have built evals or benchmarks, and you reach for a measurement before an opinion when arguing that one approach beats another.
 </li>
 <li>
 Strong Python (async, typed interfaces, Pydantic or similar) plus the systems fundamentals to work across a polyglot codebase &mdash; processes, sandboxing, filesystems, and the ability to debug something you did not write.
 </li>
 <li>
 Demonstrated ownership and strong communication, with a track record of navigating ambiguity, setting technical direction, and working effectively with internal customers in a distributed, remote-friendly team.
 
 
 </li>
 </ul>
 Nice to Haves
 
 
 <ul>
 <li>
 Experience with MCP &mdash; building servers or clients, and designing tool interfaces that constrain what a model can do rather than trusting it not to.
 </li>
 <li>
 Sandboxing and host isolation experience: process supervision, network and filesystem boundaries, resource leases, and the operational reality of macOS toolchains, Xcode, and iOS simulators.
 </li>
 <li>
 Release engineering background &mdash; bundling, artifact provenance, benchmarking against a baseline, staged promotion, and rollback you have actually rehearsed.
 </li>
 <li>
 Observability and cost accounting at scale, particularly OpenTelemetry, and experience making a spend number trustworthy enough to enforce budgets against.
 </li>
 <li>
 Inference infrastructure experience: model routing and serving (vLLM or similar), prefix caching behavior, GPU capacity planning, or running open-weight models on owned hardware.
 </li>
 <li>
 Fine-tuning or post-training experience with open-weight models, and a view on when it is worth the cost.
 </li>
 <li>
 Familiarity with Rust, Swift, or Kotlin &mdash; enough to build tooling that has to understand the repositories it operates on.
 </li>
 <li>
 A track record in fast-growing or startup environments, including 0&rarr;1 platform work where adoption had to be earned team by team rather than mandated.
 
 
 </li>
 </ul>
 
 The Benefits Of Building With Us
 
 
 
 We offer competitive salaries and meaningful equity. We believe everyone on the team should have a stake in what we&rsquo;re building. Benefits vary by region to make sure you're covered in the ways that matter most. In the US, that includes health, dental, vision, life, and disability insurance, plus a 401(k) and flexible spending accounts.
 
 
 Regardless of where you live, everyone at Ditto can utilize flexible time off. And while we work remotely, our Atlanta office is always open if you ever want a place to work or meet up with teammates.
 
 
 
 Apply Anyway
 
 
 
 At Ditto, we know game-changers don&rsquo;t always come wrapped in a &ldquo;perfect&rdquo; resume. Years of experience? Every single bullet point checked? Meh. That&rsquo;s not what drives us.
 
 
 What does matter?
 
 
 <ul>
 <li>
 Grit.
 </li>
 <li>
 Curiosity.
 </li>
 <li>
 Adaptability.
 </li>
 <li>
 And a genuine spark for what we&rsquo;re building.
 
 
 </li>
 </ul>
 So if you&rsquo;re fired up about our mission but not sure you tick every box - hit that apply button anyway. Use your application to show us how you&rsquo;ll make an impact here.
 
 
 We&rsquo;re always on the lookout for exceptional humans who want to grow, stretch, and build something meaningful with us.
 
 
 
 Equal Opportunity Employer
 
 
 
 Ditto is proud to be an equal-opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristics. Ditto is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please let us know.
</div>

AI Engineer

Explore 4+ Video production specialist in Washington this September. Find roles across top companies and apply now to boost your career.

4 video production specialist jobs In Washington

Machine Learning Engineer II (Servicing ML)

Lead Software Engineer - AI

Applied AI Engineer Intern – Summer 2027 (May/June Start)

AI Engineer