Entry Level Applied Scientist Jobs
New grad applied scientist jobs are open to recent graduates and entry level candidates with zero to two years of experience, where a strong portfolio or internship project can matter more than a long resume. Most openings are on-site and hybrid roles across Technology & Software, Artificial Intelligence, and Insurance, with employers like Amazon, TikTok, and Optum hiring at this level now.
Find JobsOverview
Showing 5 of 31+ Entry Level Applied Scientist jobs
DESCRIPTION
As an Applied Scientist on the OMHS Software Controls and Science team, you will build and deploy first-of-its-kind physical AI capabilities within Amazon Manufacturing Services. You will turn applied research into functional prototypes and production systems that operate on real parts under real shop floor conditions. This role combines applied ML, 3D perception, and geometric reasoning with a strong manufacturing-outcome focus. It will be your job to frame ambiguous fabrication problems as tractable scientific problems, and to deploy perception and part-recognition systems on robotic welding cells that match physical parts to their CAD models and determine orientation, tooling, and fixturing without manual programming. You will own the full loop from prototype to measurable result: instrumenting robotic cells with sensors, collecting real-world manufacturing data, training and iterating models against accuracy and cycle-time targets, and integrating your work into robot motion planning and production software pipelines. Your near-term mission is to help enable a lossless digital thread from engineering specification to autonomous robotic execution, starting with welding, in a high-mix environment scaling toward high-volume production.
Key job responsibilities
-
Deploy 3D perception and part-recognition systems on robotic welding cells that match physical parts to their CAD models and determine part orientation, tooling, and fixturing without manual programming.
-
Build software pipelines that connect CAD and engineering-drawing interpretation to robot motion planning and execution in a production manufacturing environment.
-
Frame ambiguous fabrication problems as tractable scientific problems, and prototype solutions end to end — from sensor setup and data collection to model training, deployment, and performance evaluation.
-
Evaluate, recommend, and integrate commercial robotic platforms, 3D scanning systems, and sensor hardware to support physical AI development on the shop floor.
-
Instrument robotic cells, collect real-world manufacturing data, and iterate on model performance against measurable accuracy and cycle-time targets.
-
Collaborate across automation engineering and software engineering teams to integrate your solutions into the shop floor deployment architecture.
About the team
Amazon is building next generation software, hardware, and processes that will run our global network of fulfillment centers that move millions of units of inventory, and ensure customers get what they want when promised.
The Science Software team in the One MHS organization unlocks Material Handling Equipment (MHE) innovation through a multiplicity of disciplines within Artificial Intelligence (AI) and applied science, including Computer Vision (CV), Physics-Informed Neural Networks (PINNs), Optimization, Reinforcement Learning, classical Machine Learning, statistical modeling, and sensing-hardware prototyping. Rooted in first principles aligned experimentation, the team is dedicated to building self-optimizing fulfillment centers, developing the models that drive real-time, building-wide orchestration of MHE. We conduct experiments, develop models, and apply machine learning (ML) at scale to optimize throughput, flow, merge, and congestion control, and to improve operational performance across the fulfillment network.
BASIC QUALIFICATIONS
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- 1+ years of deep learning, computer vision, human robotic interaction, algorithms implementation experience
- Hands-on experience deploying robots or autonomous systems in real-world environments.
- Ability to debug the full stack from perception to control.
PREFERRED QUALIFICATIONS
- Experience with robotic manipulation platforms.
- Experience with realtime sensor fusion (e.g. LiDAR, camera, radar).
- Publications in your field (CVPR, ICCV, RSS, ICRA preferred).
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, MA, Boston - 142,800.00 - 193,200.00 USD annually
USA, MA, N.Reading - 142,800.00 - 193,200.00 USD annually
DESCRIPTION
As an Applied Scientist on the OMHS Software Controls and Science team, you will build and deploy first-of-its-kind physical AI capabilities within Amazon Manufacturing Services. You will turn applied research into functional prototypes and production systems that operate on real parts under real shop floor conditions. This role combines applied ML, 3D perception, and geometric reasoning with a strong manufacturing-outcome focus. It will be your job to frame ambiguous fabrication problems as tractable scientific problems, and to deploy perception and part-recognition systems on robotic welding cells that match physical parts to their CAD models and determine orientation, tooling, and fixturing without manual programming. You will own the full loop from prototype to measurable result: instrumenting robotic cells with sensors, collecting real-world manufacturing data, training and iterating models against accuracy and cycle-time targets, and integrating your work into robot motion planning and production software pipelines. Your near-term mission is to help enable a lossless digital thread from engineering specification to autonomous robotic execution, starting with welding, in a high-mix environment scaling toward high-volume production.
Key job responsibilities
-
Deploy 3D perception and part-recognition systems on robotic welding cells that match physical parts to their CAD models and determine part orientation, tooling, and fixturing without manual programming.
-
Build software pipelines that connect CAD and engineering-drawing interpretation to robot motion planning and execution in a production manufacturing environment.
-
Frame ambiguous fabrication problems as tractable scientific problems, and prototype solutions end to end — from sensor setup and data collection to model training, deployment, and performance evaluation.
-
Evaluate, recommend, and integrate commercial robotic platforms, 3D scanning systems, and sensor hardware to support physical AI development on the shop floor.
-
Instrument robotic cells, collect real-world manufacturing data, and iterate on model performance against measurable accuracy and cycle-time targets.
-
Collaborate across automation engineering and software engineering teams to integrate your solutions into the shop floor deployment architecture.
About the team
Amazon is building next generation software, hardware, and processes that will run our global network of fulfillment centers that move millions of units of inventory, and ensure customers get what they want when promised.
The Science Software team in the One MHS organization unlocks Material Handling Equipment (MHE) innovation through a multiplicity of disciplines within Artificial Intelligence (AI) and applied science, including Computer Vision (CV), Physics-Informed Neural Networks (PINNs), Optimization, Reinforcement Learning, classical Machine Learning, statistical modeling, and sensing-hardware prototyping. Rooted in first principles aligned experimentation, the team is dedicated to building self-optimizing fulfillment centers, developing the models that drive real-time, building-wide orchestration of MHE. We conduct experiments, develop models, and apply machine learning (ML) at scale to optimize throughput, flow, merge, and congestion control, and to improve operational performance across the fulfillment network.
BASIC QUALIFICATIONS
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- 1+ years of deep learning, computer vision, human robotic interaction, algorithms implementation experience
- Hands-on experience deploying robots or autonomous systems in real-world environments.
- Ability to debug the full stack from perception to control.
PREFERRED QUALIFICATIONS
- Experience with robotic manipulation platforms.
- Experience with realtime sensor fusion (e.g. LiDAR, camera, radar).
- Publications in your field (CVPR, ICCV, RSS, ICRA preferred).
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, MA, Boston - 142,800.00 - 193,200.00 USD annually
USA, MA, N.Reading - 142,800.00 - 193,200.00 USD annually
See All 31 Entry Level Applied Scientist Jobs
Find roles that match your experience and apply in just a few clicks.
Find JobsEntry Level Applied Scientist Job Market
Who's Hiring
- Amazon12
- TikTok10
- Optum1
- Granica1
Top Industries Hiring
- Technology & Software14
- Artificial Intelligence2
- Insurance1
- Medical Devices1
- Banking & Financial Services1
Entry Level Applied Scientist Jobs: Frequently Asked Questions
How do I get an entry level applied scientist job?
Focus on building a portfolio that demonstrates applied work: published models, Kaggle competition results, research projects, or a strong graduate thesis. Employers at this level look for hands-on evidence that you can frame a problem, run experiments, and interpret results. Internship experience in machine learning, data science, or research engineering gives you a significant edge over candidates with coursework alone.
Which companies hire entry level applied scientists?
Companies hiring entry level applied scientists right now include Amazon, TikTok, and Optum, based on current listings on Migrate Mate as of September 2026. Hiring at this level comes from a broad mix of technology companies, large retail and e-commerce platforms, and research-driven enterprises that maintain dedicated applied science or machine learning teams.
Are there remote entry level applied scientist jobs?
Yes, though the majority of entry level roles still expect some in-person collaboration. About 19% of entry level applied scientist openings are remote or hybrid as of September 2026, making it a realistic option for candidates who need flexibility or are relocating after graduation.
Are these new grad applied scientist jobs?
Yes. Many listings on this page are new grad and junior roles that explicitly welcome recent graduates with little or no professional experience. A new-grad-friendly posting typically accepts zero to two years of experience and treats internships, research assistantships, or a strong independent portfolio as equivalent to full-time work history.
Which industries hire the most entry level applied scientists?
Entry Level applied scientist roles concentrate in Technology & Software, Artificial Intelligence, and Insurance, based on current listings on Migrate Mate as of September 2026. These sectors drive hiring at this level because they run large-scale data and modeling infrastructure that requires a steady pipeline of junior talent to execute experiments and ship production models.