Remote AI/ML Software Engineer Jobs
Remote AI/ML Software Engineer jobs are in strong demand across the U.S., with remote-first firms and distributed engineering teams actively hiring for roles in model development, MLOps, and applied research. Industries from technology and fintech to healthcare and enterprise software are building out remote AI/ML functions, and employers currently filling these roles include Target, Meridial, and Truveta. See the openings below and apply to the ones that match your experience.
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Showing 5 of 17+ Remote AI/ML Software Engineer 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 17 Remote AI/ML Software Engineer Jobs
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Find JobsRemote AI/ML Software Engineer Job Market
Who's Hiring
Top Industries Hiring
- Technology & Software
What Employers Look For
The qualifications that appear most often in remote AI/ML software engineer jobs.
- Proficiency in Python and core ML frameworks such as PyTorch or TensorFlow
- Experience building and deploying models in production cloud environments
- Familiarity with MLOps tools including experiment tracking, model registries, and serving infrastructure
- Strong foundation in statistics, linear algebra, and machine learning theory
- Experience with large-scale data processing using Spark, SQL, or distributed compute platforms
- Bachelor's or master's degree in computer science, statistics, or a related quantitative field
Tips for Your Remote AI/ML Software Engineer Job Search
Show async collaboration in your portfolio
Remote ai/ml teams run on written communication. Document your projects with clear README files, model cards, and experiment logs that show you can communicate decisions and trade-offs in writing, not just in a live standup. Reviewers use this as a direct signal of remote readiness.
Apply early to remote roles that fit
Migrate Mate lists remote ai/ml software engineer openings from across the U.S. in one place, so you can find roles that match your stack and apply directly without sorting through listings that don't qualify. Applying early matters because competitive remote roles fill fast.
Highlight MLOps and deployment experience clearly
Remote employers can't watch you work, so your ability to own a model from training through production deployment is a trust signal. Call out experience with tools like MLflow, Kubeflow, SageMaker, or similar platforms explicitly in your materials, not buried in a skills list.
Prepare for async-first remote interviews
Many remote ai/ml teams conduct take-home technical assessments before or instead of live coding screens. Practice writing up your approach and trade-offs clearly, since remote hiring managers evaluate both your solution and how well you explain your reasoning without real-time back-and-forth.
Remote AI/ML Software Engineer Jobs: Frequently Asked Questions
How do I get a remote ai/ml software engineer job?
Remote ai/ml software engineer roles go to candidates who can demonstrate strong async communication and self-directed execution, not just technical depth. Employers screen for experience with MLOps pipelines, model deployment, and version control in distributed environments. A public portfolio of end-to-end ML projects, clear written documentation habits, and familiarity with async collaboration tools give you a concrete edge over candidates with equivalent skills but no remote signal.
Which companies hire remote ai/ml software engineers?
Employers currently hiring remote ai/ml software engineers include Target, Meridial, and Truveta, per current remote listings on Migrate Mate as of November 2026. Remote-first technology companies, AI-native startups, and distributed enterprise engineering teams account for the largest share of these openings, with particular concentration in SaaS, fintech, and digital health.
Can you get a remote ai/ml software engineer job with no experience?
Yes, but remote entry-level ai/ml roles are harder to land because employers expect you to operate independently from day one without in-person mentorship. Your strongest substitute for experience is a portfolio of deployed projects, Kaggle competition results, or open-source contributions that show you can build and ship models end to end. Smaller AI-native startups and remote-first product companies are more likely to take a chance on junior candidates with demonstrated output.
Do you need a degree for remote ai/ml software engineer jobs?
Not always. Many remote employers care more about what you've built and deployed than which institution awarded your degree. A strong portfolio covering model training, evaluation, and production deployment, combined with proficiency in Python, PyTorch or TensorFlow, and cloud ML platforms, can outweigh a missing or unrelated degree. Senior roles and research-heavy positions at larger companies do still favor advanced degrees in computer science, statistics, or a related field.
Which industries hire the most remote ai/ml software engineers?
Most remote ai/ml software engineer openings sit in Technology & Software, per current remote listings on Migrate Mate as of November 2026. These sectors rely on distributed engineering teams that build and iterate on models without centralized office infrastructure, making remote ai/ml roles a natural fit for how they operate.
See All 17 Remote AI/ML Software Engineer Jobs
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