Machine Learning Scientist Visa Sponsorship Jobs in New York
New York is one of the top states for machine learning scientist roles, with major employers including Google, Meta, IBM, Bloomberg, and a dense cluster of fintech and healthtech firms in Manhattan. Research institutions like NYU and Columbia also drive demand. Most roles are concentrated in New York City, with a growing presence in Brooklyn's tech corridor.
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Get Access To All JobsINTRODUCTION
Passionate about precision medicine and advancing the healthcare industry?
Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time.
ROLE AND RESPONSIBILITIES
Machine Learning Scientist, Applied Machine Learning and Agentic AI, Pharma R& D
Location: New York, NY
The Machine Learning Scientist, Applied Machine Learning and Agentic AI will contribute to the technical development of cutting-edge agentic frameworks designed to automate the discovery of novel prognostic and predictive models in oncology. This role sits at the intersection of advanced Large Language Model (LLM) orchestration and computational biology. You will be responsible for building and refining "deep agents" capable of hypothesis generation, experimental design, and multimodal ML modeling utilizing foundation models.
In this role, you will be a key technical contributor, working closely with senior scientists and engineers to implement system designs and ensure code quality. You will apply advanced scientific methodologies to develop new predictive models and utilize causal inference frameworks to analyze vast multimodal oncology data, helping to scale scientific discovery from a manual process to a high-throughput, automated engine.
Description
Data Expertise: Tempus has one of the largest multimodal patient datasets ever collected, providing a unique opportunity to work with extensive and diverse data. Become an expert in Tempus’ vast epidemiological, clinical, genomic, transcriptomic and pathology imaging data, along with the latest tools and techniques for their analysis and modeling.
Teamwork and collaboration:
- Work with Research, Engineering & Data Science teams across Tempus’ expansive data science community to develop and deliver innovative computational solutions.
- Co-develop solutions with Pharma partner science and clinical teams.
Drug R&D Expertise: Work with leading pharmaceutical companies. Gain proficiency in their strategies, drug modalities, and pipelines to identify where the Tempus platform can add value.
Scientific Communication: Skillfully navigate client interactions to extract and communicate the most impactful insights driving new R&D opportunities; effectively communicate complex technical results and methodologies to diverse external stakeholders.
Personal development: Continuously immerse yourself in the latest industry trends, best practices, and advancements in machine learning and AI to revolutionize drug R&D.
Responsibilities
- Agentic AI: Develop complex, state-of-the-art agentic workflows. Build agents capable of long-horizon planning, tool use and "co-scientist" reasoning.
- Multimodal Modeling: Leverage oncology foundation models to integrate DNA, RNA, H&E, and clinical data into predictive algorithms.
- Scientific Innovation: Collaborate with clinical scientists and pharma partners to define high-value use cases, such as clinical trial design support and treatment de-escalation.
BASIC QUALIFICATIONS
Education and experience:
Minimum: PhD (or Masters degree with 3+ years of relevant experience).
Combining:
- Quantitative and computational skills, specifically in AI agent based workflows (e.g. Applied Machine Learning, Generative AI, Mathematics, biostatistics).
- Biological, medical, or drug development knowledge and data (e.g. oncology, RWE, medical science, or clinical drug development).
Technical/Scientific Skills:
- Agentic Frameworks: Proficiency in Python and orchestration frameworks, specifically LangGraph (strongly preferred) or similar. Experience building deep agents with complex state management and graphs.
- LLM Application: Deep knowledge of prompt engineering, RAG (Retrieval-Augmented Generation), function calling, and evaluating non-deterministic LLM outputs.
- Machine Learning: Strong foundation in survival analysis (CoxPH, RSF) and evaluation metrics for oncology models.
- Software Engineering: Adherence to software best practices (unit testing, git) and experience designing scalable systems.
Experience working with clinical trial or real-world data, clinical guidelines (e.g., NCCN for oncology) and emerging RWE methodologies.
Track record of success: proven in peer reviewed publications or other proven impact.
Communication Skills: Excellent written and verbal communication skills, with the ability to present complex information clearly and persuasively to diverse audiences.
Motivated: Thrive in a fast-paced environment and willing to shift priorities seamlessly.
PREFERRED QUALIFICATIONS
- Experience in integrative modeling of multi-modal clinical and omics data, preferably with multimodal embeddings and foundation models.
- Strong understanding of data and artificial intelligence in Oncology.
- Understanding of cancer biology and clinical data.
- Experience with deploying ML models in cloud environments.
COMPENSATION
- CHI: $100,000-$150,000
- NYC/SF: $120,000-$160,000
The expected salary range above is applicable if the role is performed from California and may vary for other locations (Colorado, Illinois, New York). Actual salary may vary based on qualifications and experience. Tempus offers a full range of benefits, which may include incentive compensation, restricted stock units, medical and other benefits depending on the position.
Additionally, for remote roles open to individuals in unincorporated Los Angeles – including remote roles – Tempus reasonably believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment: engaging positively with customers and other employees; accessing confidential information, including intellectual property, trade secrets, and protected health information; and appropriately handling such information in accordance with legal and ethical standards. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
About us
Tempus was founded in August of 2015 by Eric Lefkofsky, after his wife was diagnosed with Breast Cancer. Shortly after he founded the company in an effort to bring the power of technology and artificial intelligence to cancer care, he convinced Ryan Fukushima to join as the company’s first employee. Ryan and Eric began assembling a world class team, focused on building the first version of a platform capable of ingesting real time healthcare data in an effort to personalize diagnostics.
We built the platform for oncology and have expanded it to neuropsychiatry, cardiology, infectious disease (through COVID), and radiology. Despite our rapid growth, our mission remains the same—to help make sure patients are on the right drug at the right time, so they can live longer and healthier lives.
WHY WORK HERE?
We’re looking for people who can change the world.
Who question the status quo and don’t shy away from tough problems. For the builders who are never done building and the learners who are never done learning. We’re looking for passionate people with undying curiosity. Those who want to attack one of the most challenging problems mankind has ever faced. Head on.
INTRODUCTION
Passionate about precision medicine and advancing the healthcare industry?
Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time.
ROLE AND RESPONSIBILITIES
Machine Learning Scientist, Applied Machine Learning and Agentic AI, Pharma R& D
Location: New York, NY
The Machine Learning Scientist, Applied Machine Learning and Agentic AI will contribute to the technical development of cutting-edge agentic frameworks designed to automate the discovery of novel prognostic and predictive models in oncology. This role sits at the intersection of advanced Large Language Model (LLM) orchestration and computational biology. You will be responsible for building and refining "deep agents" capable of hypothesis generation, experimental design, and multimodal ML modeling utilizing foundation models.
In this role, you will be a key technical contributor, working closely with senior scientists and engineers to implement system designs and ensure code quality. You will apply advanced scientific methodologies to develop new predictive models and utilize causal inference frameworks to analyze vast multimodal oncology data, helping to scale scientific discovery from a manual process to a high-throughput, automated engine.
Description
Data Expertise: Tempus has one of the largest multimodal patient datasets ever collected, providing a unique opportunity to work with extensive and diverse data. Become an expert in Tempus’ vast epidemiological, clinical, genomic, transcriptomic and pathology imaging data, along with the latest tools and techniques for their analysis and modeling.
Teamwork and collaboration:
- Work with Research, Engineering & Data Science teams across Tempus’ expansive data science community to develop and deliver innovative computational solutions.
- Co-develop solutions with Pharma partner science and clinical teams.
Drug R&D Expertise: Work with leading pharmaceutical companies. Gain proficiency in their strategies, drug modalities, and pipelines to identify where the Tempus platform can add value.
Scientific Communication: Skillfully navigate client interactions to extract and communicate the most impactful insights driving new R&D opportunities; effectively communicate complex technical results and methodologies to diverse external stakeholders.
Personal development: Continuously immerse yourself in the latest industry trends, best practices, and advancements in machine learning and AI to revolutionize drug R&D.
Responsibilities
- Agentic AI: Develop complex, state-of-the-art agentic workflows. Build agents capable of long-horizon planning, tool use and "co-scientist" reasoning.
- Multimodal Modeling: Leverage oncology foundation models to integrate DNA, RNA, H&E, and clinical data into predictive algorithms.
- Scientific Innovation: Collaborate with clinical scientists and pharma partners to define high-value use cases, such as clinical trial design support and treatment de-escalation.
BASIC QUALIFICATIONS
Education and experience:
Minimum: PhD (or Masters degree with 3+ years of relevant experience).
Combining:
- Quantitative and computational skills, specifically in AI agent based workflows (e.g. Applied Machine Learning, Generative AI, Mathematics, biostatistics).
- Biological, medical, or drug development knowledge and data (e.g. oncology, RWE, medical science, or clinical drug development).
Technical/Scientific Skills:
- Agentic Frameworks: Proficiency in Python and orchestration frameworks, specifically LangGraph (strongly preferred) or similar. Experience building deep agents with complex state management and graphs.
- LLM Application: Deep knowledge of prompt engineering, RAG (Retrieval-Augmented Generation), function calling, and evaluating non-deterministic LLM outputs.
- Machine Learning: Strong foundation in survival analysis (CoxPH, RSF) and evaluation metrics for oncology models.
- Software Engineering: Adherence to software best practices (unit testing, git) and experience designing scalable systems.
Experience working with clinical trial or real-world data, clinical guidelines (e.g., NCCN for oncology) and emerging RWE methodologies.
Track record of success: proven in peer reviewed publications or other proven impact.
Communication Skills: Excellent written and verbal communication skills, with the ability to present complex information clearly and persuasively to diverse audiences.
Motivated: Thrive in a fast-paced environment and willing to shift priorities seamlessly.
PREFERRED QUALIFICATIONS
- Experience in integrative modeling of multi-modal clinical and omics data, preferably with multimodal embeddings and foundation models.
- Strong understanding of data and artificial intelligence in Oncology.
- Understanding of cancer biology and clinical data.
- Experience with deploying ML models in cloud environments.
COMPENSATION
- CHI: $100,000-$150,000
- NYC/SF: $120,000-$160,000
The expected salary range above is applicable if the role is performed from California and may vary for other locations (Colorado, Illinois, New York). Actual salary may vary based on qualifications and experience. Tempus offers a full range of benefits, which may include incentive compensation, restricted stock units, medical and other benefits depending on the position.
Additionally, for remote roles open to individuals in unincorporated Los Angeles – including remote roles – Tempus reasonably believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment: engaging positively with customers and other employees; accessing confidential information, including intellectual property, trade secrets, and protected health information; and appropriately handling such information in accordance with legal and ethical standards. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
About us
Tempus was founded in August of 2015 by Eric Lefkofsky, after his wife was diagnosed with Breast Cancer. Shortly after he founded the company in an effort to bring the power of technology and artificial intelligence to cancer care, he convinced Ryan Fukushima to join as the company’s first employee. Ryan and Eric began assembling a world class team, focused on building the first version of a platform capable of ingesting real time healthcare data in an effort to personalize diagnostics.
We built the platform for oncology and have expanded it to neuropsychiatry, cardiology, infectious disease (through COVID), and radiology. Despite our rapid growth, our mission remains the same—to help make sure patients are on the right drug at the right time, so they can live longer and healthier lives.
WHY WORK HERE?
We’re looking for people who can change the world.
Who question the status quo and don’t shy away from tough problems. For the builders who are never done building and the learners who are never done learning. We’re looking for passionate people with undying curiosity. Those who want to attack one of the most challenging problems mankind has ever faced. Head on.
Machine Learning Scientist Job Roles in New York
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Search Machine Learning Scientist Jobs in New YorkMachine Learning Scientist Jobs in New York: Frequently Asked Questions
Which companies sponsor visas for machine learning scientists in New York?
Large technology and financial firms are the most consistent sponsors. Google, Meta, Amazon, IBM, and Microsoft all have significant New York operations and established visa sponsorship programs for machine learning scientists. Bloomberg, Two Sigma, and other fintech firms also regularly sponsor H-1B visa petitions for these roles. Healthtech companies and research-focused organizations like Memorial Sloan Kettering have become active sponsors as well.
Which visa types are most common for machine learning scientist roles in New York?
The H-1B is the most common visa for machine learning scientists in New York, given that the role clearly meets the specialty occupation standard requiring a bachelor's degree or higher in computer science, statistics, or a related field. Candidates with extraordinary recognition in the field may qualify for the O-1A. Those already holding an advanced degree from a U.S. university may also have employer-sponsored EB-2 or EB-3 green card pathways initiated alongside their nonimmigrant status.
How to find machine learning scientist visa sponsorship jobs in New York?
Migrate Mate is built specifically for international candidates seeking visa sponsorship and lets you filter machine learning scientist roles by state, so you can focus directly on New York employers who are open to sponsoring. Because sponsorship intent isn't always stated in a job listing, Migrate Mate surfaces roles from companies with a documented history of filing H-1B petitions for machine learning and AI positions, saving significant research time.
Which cities in New York have the most machine learning scientist sponsorship jobs?
New York City accounts for the overwhelming majority of machine learning scientist sponsorship activity in the state. Manhattan, particularly Midtown and the Flatiron District, is home to most of the large tech and finance employers. Brooklyn's DUMBO and Industry City areas have a growing concentration of AI startups and research labs. Buffalo and Albany have a smaller but emerging presence, driven by state-funded technology initiatives and university research partnerships.
Are there state-specific factors that affect visa sponsorship for machine learning scientists in New York?
New York employers filing Labor Condition Applications must pay the prevailing wage for the specific metropolitan area where the work is performed, and New York City prevailing wages for machine learning scientists are among the highest in the country. The dense concentration of H-1B-dependent employers in finance and tech means competition for sponsorship slots is real, and companies in these sectors tend to initiate the process well before the April H-1B filing window. NYU, Columbia, and Cornell Tech produce a significant pipeline of candidates, which shapes how employers recruit.
What is the prevailing wage for sponsored machine learning scientist jobs in New York?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.