Entry Level Technical Research Assistant Jobs
New grad technical research assistant jobs welcome recent graduates and entry level candidates with zero to two years of experience, where strong internship work or an academic research portfolio can matter more than a long resume. Most openings blend on-site and remote settings across Technology & Software, Education, and Science & Research, with employers like Liquid AI, Perplexity, and Ataraxis AI hiring at this level now.
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See related jobsAbout Ataraxis AI
Ataraxis is a clinical AI research lab working at the intersection of multi-modal AI and precision medicine. Our goal is to make disease predictable. To accomplish this, we develop new AI methods that predict patient outcomes and treatment response, and build clinical tools to assist physicians in selecting the most optimal treatments for their patients. Our AI research lab discovers and develops methods to recognize patterns and predict outcomes across complex, multi-modal clinical data. This spans our causality (Ataraxis™ Tau), foundation model (Falcon and Kestrel for digital pathology), and survival analysis research. Our first clinical products, such as Ataraxis™ Breast for breast cancer, already help patients get the most appropriate treatment across the best academic institutions and community clinics worldwide. At Ataraxis, you will have a unique opportunity to shape not only the future of our company, but also the future of healthcare. You will join an exceptional team at the forefront of clinical AI research and deployment. Our advisors include AI pioneers such as our founding advisor, Yann LeCun, and distinguished oncologists from top cancer research institutions, all united by the mission to redefine precision medicine. Ataraxis has raised over $24 million in funding, including a $20 million Series A led by top venture capital funds such as Thiel Capital/Founders Fund (OpenAI, SpaceX, Palantir), Obvious Ventures (AMI Labs, Inceptive, Radical Numerics, Recursion), and AIX Ventures (Hugging Face, Perplexity). We are a company with a flat organizational structure, where every team member is empowered to actively contribute. Leadership roles are earned by those who demonstrate initiative and consistently deliver exceptional results. Strong work ethic and the ability to prioritize ruthlessly are essential.
Responsibilities
- Implement novel machine learning models and methods for self-supervised learning, survival analysis, multi-modal learning, causality and interpretability.
- Translate machine learning and statistics papers into production-ready code.
- Build robust model evaluation frameworks and monitor model performance.
- Develop pipelines for data preprocessing, integration, and quality assurance.
- Maintain high standards of scientific documentation to ensure reproducibility and clarity in both internal reports and external publications.
- Optimize code to run efficiently on GPU clusters, with emphasis on speed and scalability.
- Deploy machine learning models to the cloud in optimized inference pipelines.
- Develop and maintain regression and unit tests to ensure high-quality code.
- Disseminate the results by co-authoring research papers and abstracts.
- Collaborate with a multidisciplinary team of engineers and scientists.
Qualifications
- BS/MS/PhD degree in computer science, machine learning or statistics.
- Excellent understanding of core machine learning concepts.
- Excellent knowledge of the foundations of statistics, linear algebra and probability.
- Excellent skills in Python and PyTorch.
- Proficiency in data visualization and communicating complex results to both technical and non-technical audiences.
- Excellent understanding of computer architecture, parallel training of AI models, and GPU optimization.
- Experience in deep learning. Experience in at least one of {self-supervised learning, survival analysis, multi-modal learning, domain adaptation, causal inference, model interpretability, computational pathology} is a plus but is not critical.
- Attention to detail and ability to drive tasks to completion.
- Passion for research. Prior publications in A* conferences (e.g. ICML, ICLR, NeurIPS, CVPR) are a plus but are not critical.
Compensation Range: $120K - $210K
About Ataraxis AI
Ataraxis is a clinical AI research lab working at the intersection of multi-modal AI and precision medicine. Our goal is to make disease predictable. To accomplish this, we develop new AI methods that predict patient outcomes and treatment response, and build clinical tools to assist physicians in selecting the most optimal treatments for their patients. Our AI research lab discovers and develops methods to recognize patterns and predict outcomes across complex, multi-modal clinical data. This spans our causality (Ataraxis™ Tau), foundation model (Falcon and Kestrel for digital pathology), and survival analysis research. Our first clinical products, such as Ataraxis™ Breast for breast cancer, already help patients get the most appropriate treatment across the best academic institutions and community clinics worldwide. At Ataraxis, you will have a unique opportunity to shape not only the future of our company, but also the future of healthcare. You will join an exceptional team at the forefront of clinical AI research and deployment. Our advisors include AI pioneers such as our founding advisor, Yann LeCun, and distinguished oncologists from top cancer research institutions, all united by the mission to redefine precision medicine. Ataraxis has raised over $24 million in funding, including a $20 million Series A led by top venture capital funds such as Thiel Capital/Founders Fund (OpenAI, SpaceX, Palantir), Obvious Ventures (AMI Labs, Inceptive, Radical Numerics, Recursion), and AIX Ventures (Hugging Face, Perplexity). We are a company with a flat organizational structure, where every team member is empowered to actively contribute. Leadership roles are earned by those who demonstrate initiative and consistently deliver exceptional results. Strong work ethic and the ability to prioritize ruthlessly are essential.
Responsibilities
- Implement novel machine learning models and methods for self-supervised learning, survival analysis, multi-modal learning, causality and interpretability.
- Translate machine learning and statistics papers into production-ready code.
- Build robust model evaluation frameworks and monitor model performance.
- Develop pipelines for data preprocessing, integration, and quality assurance.
- Maintain high standards of scientific documentation to ensure reproducibility and clarity in both internal reports and external publications.
- Optimize code to run efficiently on GPU clusters, with emphasis on speed and scalability.
- Deploy machine learning models to the cloud in optimized inference pipelines.
- Develop and maintain regression and unit tests to ensure high-quality code.
- Disseminate the results by co-authoring research papers and abstracts.
- Collaborate with a multidisciplinary team of engineers and scientists.
Qualifications
- BS/MS/PhD degree in computer science, machine learning or statistics.
- Excellent understanding of core machine learning concepts.
- Excellent knowledge of the foundations of statistics, linear algebra and probability.
- Excellent skills in Python and PyTorch.
- Proficiency in data visualization and communicating complex results to both technical and non-technical audiences.
- Excellent understanding of computer architecture, parallel training of AI models, and GPU optimization.
- Experience in deep learning. Experience in at least one of {self-supervised learning, survival analysis, multi-modal learning, domain adaptation, causal inference, model interpretability, computational pathology} is a plus but is not critical.
- Attention to detail and ability to drive tasks to completion.
- Passion for research. Prior publications in A* conferences (e.g. ICML, ICLR, NeurIPS, CVPR) are a plus but are not critical.
Compensation Range: $120K - $210K
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Entry Level Technical Research Assistant Jobs: Frequently Asked Questions
How do I get an entry level technical research assistant job?
Entry level technical research assistant roles typically look for candidates with relevant coursework, lab or research experience, and demonstrated data-gathering or analytical skills. Internships, undergraduate research projects, or independent studies that show hands-on methodology work give candidates a clear edge. Tailoring your resume to highlight specific research tools, software, or subject-matter knowledge relevant to each employer's field strengthens every application at this stage.
Which companies hire entry level technical research assistants?
Companies hiring entry level technical research assistants right now include Liquid AI, Perplexity, and Ataraxis AI, based on current listings on Migrate Mate as of November 2026. Hiring at this level comes from a wide range of employers, including research institutions, technology firms, healthcare organizations, and consulting groups that build out junior research teams with new and recent graduates.
Are there remote entry level technical research assistant jobs?
Yes, though most positions still favor on-site or hybrid arrangements. About 20% of entry level technical research assistant openings are remote or hybrid as of November 2026, reflecting roles where data analysis, literature reviews, and reporting tasks can be completed off-site. Fully remote positions at this level tend to be more competitive, so applying broadly across work-setting types improves your chances.
Are these new grad technical research assistant jobs?
Yes, these listings include new grad, recent graduate, and junior technical research assistant roles. A new grad friendly posting typically welcomes candidates with zero to two years of experience, accepts internships or academic research in place of full-time work history, and does not require advanced credentials. Look for language like 'entry level,' 'junior researcher,' or 'recent graduates encouraged to apply' as reliable signals.
Which industries hire the most entry level technical research assistants?
Entry Level technical research assistant roles concentrate in Technology & Software, Education, and Science & Research, based on current listings on Migrate Mate as of November 2026. These sectors drive hiring at this level because they maintain active research pipelines that rely on junior staff to support data collection, literature synthesis, and preliminary analysis across ongoing projects.