Remote AI/ML Researcher Jobs
Remote AI/ML Researcher jobs are in active demand across the U.S., with remote-first firms and distributed research teams hiring across tech, healthcare, and enterprise software. Employers hiring remotely right now include Target, Meridial, and Cobalt. Find a role that fits below and apply directly.
Find Remote AI/ML Researcher JobsOverview
Showing 5 of 23+ Remote AI/ML Researcher jobs
Pay is based on several factors which vary based on position. These include labor markets and in some instances may include education, work experience and certifications. In addition to your pay, Target cares about and invests in you as a team member, so that you can take care of yourself and your family. Target offers eligible team members and their dependents comprehensive health benefits and programs, which may include medical, vision, dental, life insurance and more, to help you and your family take care of your whole selves. Other benefits for eligible team members include 401(k), employee discount, short term disability, long term disability, paid sick leave, paid national holidays, and paid vacation. Find competitive benefits from financial and education to well-being and beyond at https://corporate.target.com/careers/benefits.
JOIN TARGET AS A LEAD ENGINEER – FORWARD DEPLOYED ENGINEERING - AI PLATFORMS
About Us:
Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here.
As a Lead Forward Deployed Engineer - AI Platforms (FDE), you will help accelerate the adoption of Target's enterprise AI platform by working with product and engineering teams to solve complex technical challenges, enable platform capabilities, and help teams build and operate production-grade AI applications. You will operate at the intersection of AI engineering, platform engineering, and product development bringing technical expertise in software architecture, distributed systems, LLMs, and agentic systems. You will combine hands-on engineering with technical guidance, solution architecture, and development of reusable tools and solutions that improve how teams adopt and use the enterprise AI platform
A key part of this role is learning from real-world implementations and using those insights to improve the broader AI platform. You will collaborate across engineering teams to identify recurring challenges, address adoption friction, and help translate successful implementation patterns into scalable platform capabilities.
As a Lead FDE Engineer, you bring broad technical expertise and help guide complex engineering efforts across teams and systems. You can independently design and implement production-grade architectures while improving the effectiveness of others through technical guidance, engineering practices, and collaborative problem-solving. You help teams navigate architectural tradeoffs, raise engineering quality, and connect technical decisions to long-term platform and product outcomes.
As a Lead Engineer within Forward Deployed Engineering, you’ll:
- Lead complex technical engagements that accelerate enterprise AI platform adoption, combining solution architecture, hands-on engineering, and technical guidance to help teams move from experimentation to production
- Design, build, and productionize AI solutions, reference implementations, technical tooling, and platform-support capabilities using LLMs, agentic architectures, enterprise context and retrieval, model APIs, and tool integrations
- Guide technical design and implementation across engineering efforts, helping teams navigate complex architectural decisions, troubleshoot challenges, and develop scalable, maintainable solutions
- Apply software engineering and distributed systems expertise to improve the reliability, security, performance, observability, and op readiness of production AI systems
- Identify recurring implementation challenges, integration gaps, and platform limitations, collaborating with platform engineering to develop reusable patterns, APIs, SDKs, frameworks, and shared capabilities
- Help establish and improve engineering practices across engagements - including architecture reviews, code quality, testing, evaluation, deployment, and prod ops
- Collaborate across product, engineering, and platform teams to evaluate technical approaches, share implementation learnings, and improve how teams adopt and use enterprise AI capabilities
Core responsibilities of this job are described within this job description. Job duties may change at any time due to business needs.
About you:
- 4-year degree or equivalent experience
- 5+ years of software development experience with strong hands-on engineering and programming skills
- Expertise in software architecture, design, distributed systems, APIs, cloud-native technologies and modern engineering practices
- Demonstrated proficiency programming in Java, Python, Koltin, etc.
- Hands-on experience building and productionizing AI apps using LLMs, agentic architectures, model APIs, retrieval/context patterns, tool integration and evaluation frameworks
- Demonstrated ability to lead complex technical initiatives from design through production, guide architectural decisions, and navigate ambiguous engineering challenges across teams or systems
- Experience with production engineering practices, including CI/CD, testing, observability, reliability, performance, security, and ops
- Experience developing reusable engineering patterns, technical tooling, reference implementations, APIs, SDKs, or platform capabilities that improve platform adoption and engineering efficiency
- Ability to provide technical guidance, influence engineering decisions, and improve engineering practices through collaboration, architecture reviews, and knowledge sharing
- Effective communication and technical judgment, with the ability to evaluate tradeoffs and collaborate across product, engineering, and platform teams
- Maintains technical knowledge within areas of expertise and stays current with rapidly evolving AI and software engineering technologies through formal training and self-directed learning.
This position will operate as a Hybrid/Flex for Your Day work arrangement based on Target’s needs. A Hybrid/Flex for Your Day work arrangement means the team member’s core role will need to be performed both onsite at the Target HQ MN location the role is assigned to and virtually, depending upon what your role, team and tasks require for that day. Work duties cannot be performed outside of the country of the primary work location, unless otherwise prescribed by Target. Click here if you are curious to learn more about Minnesota.
Benefits Eligibility
Please paste this url into your preferred browser to learn about benefits eligibility for this role: https://tgt.biz/BenefitsForYou_EAmericans with Disabilities Act (ADA)
In compliance with state and federal laws, Target will make reasonable accommodations for applicants with disabilities. If a reasonable accommodation is needed to participate in the job application or interview process, please reach out to candidate.accommodations@HRHelp.Target.com. Non-accommodation-related requests, such as application follow-ups or technical issues, will not be addressed through this channel.
Application deadline is : 12/10/2026Pay is based on several factors which vary based on position. These include labor markets and in some instances may include education, work experience and certifications. In addition to your pay, Target cares about and invests in you as a team member, so that you can take care of yourself and your family. Target offers eligible team members and their dependents comprehensive health benefits and programs, which may include medical, vision, dental, life insurance and more, to help you and your family take care of your whole selves. Other benefits for eligible team members include 401(k), employee discount, short term disability, long term disability, paid sick leave, paid national holidays, and paid vacation. Find competitive benefits from financial and education to well-being and beyond at https://corporate.target.com/careers/benefits.
JOIN TARGET AS A LEAD ENGINEER – FORWARD DEPLOYED ENGINEERING - AI PLATFORMS
About Us:
Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here.
As a Lead Forward Deployed Engineer - AI Platforms (FDE), you will help accelerate the adoption of Target's enterprise AI platform by working with product and engineering teams to solve complex technical challenges, enable platform capabilities, and help teams build and operate production-grade AI applications. You will operate at the intersection of AI engineering, platform engineering, and product development bringing technical expertise in software architecture, distributed systems, LLMs, and agentic systems. You will combine hands-on engineering with technical guidance, solution architecture, and development of reusable tools and solutions that improve how teams adopt and use the enterprise AI platform
A key part of this role is learning from real-world implementations and using those insights to improve the broader AI platform. You will collaborate across engineering teams to identify recurring challenges, address adoption friction, and help translate successful implementation patterns into scalable platform capabilities.
As a Lead FDE Engineer, you bring broad technical expertise and help guide complex engineering efforts across teams and systems. You can independently design and implement production-grade architectures while improving the effectiveness of others through technical guidance, engineering practices, and collaborative problem-solving. You help teams navigate architectural tradeoffs, raise engineering quality, and connect technical decisions to long-term platform and product outcomes.
As a Lead Engineer within Forward Deployed Engineering, you’ll:
- Lead complex technical engagements that accelerate enterprise AI platform adoption, combining solution architecture, hands-on engineering, and technical guidance to help teams move from experimentation to production
- Design, build, and productionize AI solutions, reference implementations, technical tooling, and platform-support capabilities using LLMs, agentic architectures, enterprise context and retrieval, model APIs, and tool integrations
- Guide technical design and implementation across engineering efforts, helping teams navigate complex architectural decisions, troubleshoot challenges, and develop scalable, maintainable solutions
- Apply software engineering and distributed systems expertise to improve the reliability, security, performance, observability, and op readiness of production AI systems
- Identify recurring implementation challenges, integration gaps, and platform limitations, collaborating with platform engineering to develop reusable patterns, APIs, SDKs, frameworks, and shared capabilities
- Help establish and improve engineering practices across engagements - including architecture reviews, code quality, testing, evaluation, deployment, and prod ops
- Collaborate across product, engineering, and platform teams to evaluate technical approaches, share implementation learnings, and improve how teams adopt and use enterprise AI capabilities
Core responsibilities of this job are described within this job description. Job duties may change at any time due to business needs.
About you:
- 4-year degree or equivalent experience
- 5+ years of software development experience with strong hands-on engineering and programming skills
- Expertise in software architecture, design, distributed systems, APIs, cloud-native technologies and modern engineering practices
- Demonstrated proficiency programming in Java, Python, Koltin, etc.
- Hands-on experience building and productionizing AI apps using LLMs, agentic architectures, model APIs, retrieval/context patterns, tool integration and evaluation frameworks
- Demonstrated ability to lead complex technical initiatives from design through production, guide architectural decisions, and navigate ambiguous engineering challenges across teams or systems
- Experience with production engineering practices, including CI/CD, testing, observability, reliability, performance, security, and ops
- Experience developing reusable engineering patterns, technical tooling, reference implementations, APIs, SDKs, or platform capabilities that improve platform adoption and engineering efficiency
- Ability to provide technical guidance, influence engineering decisions, and improve engineering practices through collaboration, architecture reviews, and knowledge sharing
- Effective communication and technical judgment, with the ability to evaluate tradeoffs and collaborate across product, engineering, and platform teams
- Maintains technical knowledge within areas of expertise and stays current with rapidly evolving AI and software engineering technologies through formal training and self-directed learning.
This position will operate as a Hybrid/Flex for Your Day work arrangement based on Target’s needs. A Hybrid/Flex for Your Day work arrangement means the team member’s core role will need to be performed both onsite at the Target HQ MN location the role is assigned to and virtually, depending upon what your role, team and tasks require for that day. Work duties cannot be performed outside of the country of the primary work location, unless otherwise prescribed by Target. Click here if you are curious to learn more about Minnesota.
Benefits Eligibility
Please paste this url into your preferred browser to learn about benefits eligibility for this role: https://tgt.biz/BenefitsForYou_EAmericans with Disabilities Act (ADA)
In compliance with state and federal laws, Target will make reasonable accommodations for applicants with disabilities. If a reasonable accommodation is needed to participate in the job application or interview process, please reach out to candidate.accommodations@HRHelp.Target.com. Non-accommodation-related requests, such as application follow-ups or technical issues, will not be addressed through this channel.
Application deadline is : 12/10/2026See All 23 Remote AI/ML Researcher Jobs
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Find Remote AI/ML Researcher JobsRemote AI/ML Researcher Job Market
Who's Hiring
Top Industries Hiring
- Fintech
- Technology & Software
- Investment & Asset Management
What Employers Look For
The qualifications that appear most often in remote AI/ML researcher jobs.
- PhD or Master's degree in computer science, statistics, or a related quantitative field
- Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow
- Experience designing and running experiments with large-scale datasets
- Familiarity with transformer architectures and modern foundation model techniques
- Published research or demonstrated contributions to the machine learning community
- Ability to communicate technical findings clearly to cross-functional stakeholders
Tips for Your Remote AI/ML Researcher Job Search
Document your research process publicly
Remote employers can't watch you work, so your GitHub, experiment logs, and write-ups become your proof of competence. Publish reproducible notebooks, model cards, and clear README files that show how you scope and execute research independently.
Apply early to remote roles that fit
Migrate Mate lists remote ai/ml researcher openings from across the U.S. in one place, so you can find roles that match your skills and apply directly without sorting through unrelated listings or location-filtered results.
Sharpen async written communication skills
Remote research teams rely on written updates, design docs, and Slack threads instead of whiteboard sessions. Practice writing concise experiment summaries and technical proposals that a distributed team can act on without a follow-up meeting.
Target remote-first companies specifically
Companies that built distributed from the start have stronger remote research infrastructure than those adapting office roles. Look for organizations with async-first documentation culture, established virtual onboarding, and research teams already working across multiple time zones.
Remote AI/ML Researcher Jobs: Frequently Asked Questions
How do I get a remote ai/ml researcher job?
Target companies with established distributed research teams, since they already have the infrastructure and culture for remote technical work. Remote employers screen for self-direction, strong written communication, and the ability to collaborate asynchronously across time zones. A well-documented GitHub portfolio, published research or preprints, and clear experiment write-ups give you a concrete edge over candidates who rely on in-person presence.
Which companies hire remote ai/ml researchers?
Companies hiring remote ai/ml researchers right now include Target, Meridial, and Cobalt, based on current remote listings on Migrate Mate as of November 2026. Remote-first tech firms, distributed enterprise software companies, and AI-native startups across sectors like healthcare, finance, and cloud infrastructure are among the most active hiring organizations for this role.
Can you get a remote ai/ml researcher job with no experience?
Yes, but remote entry-level roles are harder to land because you're expected to work independently from day one without in-office mentorship. Remote-first startups and research-focused open-source organizations are more open to early-career candidates. What opens the door is a documented project portfolio, contributions to open-source ML repositories, or a capstone that shows you can scope, execute, and communicate a research problem without hand-holding.
Do you need a degree for remote ai/ml researcher jobs?
Usually, but not always in the traditional sense. Most remote ai/ml researcher roles expect a graduate degree in machine learning, computer science, or a related field, particularly at research-focused companies. Remote employers increasingly weigh demonstrated output alongside credentials, so published work, reproducible code, and a strong portfolio of completed projects can complement or partially offset a non-traditional educational background.
Which industries hire the most remote ai/ml researchers?
The sectors hiring the most remote ai/ml researchers are Fintech, Technology & Software, and Investment & Asset Management, based on current remote listings on Migrate Mate as of November 2026. These sectors rely on distributed research teams to develop and iterate on models without geographic constraints, making remote ai/ml researchers a natural fit for their hiring structures.
See All 23 Remote AI/ML Researcher Jobs
Find roles that match your experience and apply in just a few clicks.
Find Remote AI/ML Researcher Jobs