Mid Level Applied Scientist Jobs
Mid level applied scientist jobs go to researchers and engineers ready to own projects end to end, drive modeling decisions with limited oversight, and bring junior team members along. Roles are spread across on-site, hybrid, and remote settings in Technology & Software, Retail, and E-Commerce & Online Marketplaces, with employers like Amazon, SentiLink, and Amazon Web Services hiring at this level now.
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DESCRIPTION
We are looking for an Applied Scientist II to build the AI behind Auto Optimization: agentic systems that automatically optimize advertisers' campaigns on their behalf. Guided by an advertiser's standing instructions, these agents observe how a campaign is performing, reason about what to change, and act on it continuously as conditions in the marketplace shift.
Optimizing a campaign well is a collection of decisions. It means working across every control an advertiser has at once: the keywords and products they target, the bids they set, the budgets they allocate, and where their ads appear, all aligned with the preferences of the advertiser. These choices are connected, since a change to targeting changes the right bid, and a change in bids changes how budget should be spent. You will build agents that make these decisions together rather than one lever at a time, and that adapt across many different campaign types and advertiser goals, from growing sales on established products to reaching new customers and launching new ones.
Working backwards from the needs of millions of advertisers, you will solve ambiguous problems, invent new methods, and deliver them into a live product that manages real campaigns. You will stay deeply hands-on with the hardest technical problems, collaborate with product and engineering partners on approach, and help raise the quality of the team's science.
Key job responsibilities
- Build agentic systems that automatically optimize campaigns on an advertiser's behalf, working holistically across every control they have (targeting, bids, budgets, and placements) rather than one lever at a time, and generalizing across many campaign types and advertiser goals, from scaling a proven product to reaching new customers and launching something new.
- Encode the dynamics of the auction and marketplace into how the agent reasons, balancing advertiser return, shopper experience, and marketplace health.
- Turn raw signal into intelligence by defining and curating the datasets that train and evaluate these agents, from campaign and marketplace data to auction and bid/budget signals, impressions, clicks, conversions, and search-term performance.
- Push the frontier of agent design, building the core of the agent itself: planning, tool use (for example, auction simulation, ML models, and optimization routines), and long-horizon reasoning across decisions that interact, and writing the production-quality, critical-path code that carries it from prototype to launch.
- Set the bar for trust by developing the evaluation and safety methods that make it trustworthy to let an agent act on live campaigns and real budgets.
- Grow with a team that grows the field: contribute to our scientific agenda, learn alongside strong scientists and engineers, and share your work with the broader community.
About the team
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through the latest generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights.
We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising.
This team within Sponsored Products and Brands is focused on guiding and supporting millions of advertisers to meet their advertising needs of creating and managing ad campaigns. At this scale, the complexity of diverse advertiser goals, campaign types, and market dynamics creates both a massive technical challenge and a transformative opportunity: even small improvements in guidance systems can have outsized impact on advertiser success and Amazon's retail ecosystem.
Our vision is to build a highly personalized, context-aware agentic advertiser guidance system that leverages LLMs together with tools such as auction simulations, ML models, and optimization algorithms. This agentic framework will operate across both chat and non-chat experiences in the ad console, scaling to natural language queries as well as autonomously managing campaigns based on deep understanding of the advertiser. To execute this vision, we collaborate closely with stakeholders across Ad Console, Sales, and Marketing to identify opportunities, from high-level product guidance down to granular keyword recommendations, and deliver them through a tailored, personalized experience. Our work is grounded in state-of-the-art agent architectures, tool integration, reasoning frameworks, and model customization approaches (including tuning, MCP, and preference optimization), ensuring our systems are both scalable and adaptive.
BASIC QUALIFICATIONS
- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
PREFERRED QUALIFICATIONS
- Experience using Unix/Linux
- Experience in professional software development
- Experience building high-velocity ad products
- Experience designing and deploying LLM-based agents in production.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
LOCATION
USA, NY, New York - 172,400.00 - 223,400.00 USD annually
USA, WA, SEATTLE - 142,800.00 - 193,200.00 USD annually
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Who's Hiring
- Amazon54

- SentiLink6

- Amazon Web Services4

- GEICO3

- Open Exchange Labs3

Top Industries Hiring
- Technology & Software34
- Retail26
- E-Commerce & Online Marketplaces23
- Distribution & Wholesale5
- Construction & Real Estate3
Mid Level Applied Scientist Jobs: Frequently Asked Questions
How do I get a mid level applied scientist job?
Position your existing work around ownership and impact rather than task completion. Highlight projects where you shaped the modeling approach, interpreted results for stakeholders, or resolved ambiguous problem definitions. Strong applications show a clear through line from your research or industry work to the team's outcomes, with concrete examples of decisions you drove independently and methods you selected or adapted.
Which companies hire mid level applied scientists?
Companies hiring mid level applied scientists right now include Amazon, SentiLink, and Amazon Web Services, based on current listings on Migrate Mate as of September 2026. Hiring at this level comes from a mix of large technology and platform companies, research-intensive enterprises in healthcare and finance, and growth-stage startups that need scientists who can work with limited supervision.
Are there remote mid level applied scientist jobs?
Yes, remote and hybrid options are well represented at this level. About 28% of mid level applied scientist openings are remote or hybrid as of September 2026, reflecting how many teams have structured applied science work to be location-flexible. On-site roles tend to cluster around hardware-adjacent research, lab environments, and organizations with strong in-person collaboration norms.
How do I move up to a mid level applied scientist role?
The path from entry level to mid level is built on deepening one or two areas of applied expertise, moving from executing assigned tasks to proposing and owning the approach. Over your first few years, take on projects where your judgment shapes the outcome, document measurable results, and seek exposure to cross-functional work. Employers recognize readiness for mid level when your contribution history shows consistent independent problem-solving.
Which industries hire the most mid level applied scientists?
Mid Level applied scientist roles concentrate in Technology & Software, Retail, and E-Commerce & Online Marketplaces, based on current listings on Migrate Mate as of September 2026. These sectors drive hiring because their core products and decisions depend directly on predictive modeling, experimentation, and data-intensive research at a scale that requires experienced contributors working without close supervision.