6,823 Remote Machine Learning Engineer Jobs (August 2026)

Extreme Networks is seeking a Principal Machine Learning Engineer with extensive experience in the software development lifecycle and deep knowledge of machine learning technologies. The successful candidate will lead the development of cutting-edge solutions in data mining and AI, working in a diverse and inclusive environment. This role offers an opportunity to impact global innovation within networking solutions and contribute to significant technological advancements. Ideal candidates will have strong programming skills, preferably in Python or Java, and proven experience in leading and mentoring teams.

Posted 1 week ago

Join a stealth AI startup backed by a leading Southeast Asian technology company, focusing on creating an AI-native communication platform. This role involves building and deploying production-grade machine learning systems and translating research into scalable solutions. You will collaborate with research and application engineering teams to deliver high-performance ML systems that function effectively in real-world production environments.

Posted 1 week ago

HubSpot seeks a Principal Machine Learning Engineer to join its AI Platform Group, focusing on building systems for AI context that enhance customer interactions across its CRM platform. This role involves defining the technical direction for applied ML and AI systems, collaborating with various teams to deliver high-impact projects. Ideal candidates will have a strong background in machine learning and experience in developing solutions that improve customer experience and product strategies.

Posted 1 week ago

The Principal Machine Learning Engineer at iHerb will create scalable machine learning systems that impact millions. Collaborating closely with business partners and various technical teams, this role aims to enhance customer experience and automate core processes by integrating machine intelligence. Key responsibilities include developing machine learning infrastructures, participating in code reviews, and researching new technologies while ensuring a strong focus on team collaboration and effective communication. Ideal candidates should have strong coding experience, familiarity with big data technologies, and at least two years of relevant experience in machine learning.

Posted 4 weeks ago

We are seeking a Principal Machine Learning Engineer to lead the design and evolution of critical ML systems. This hands-on role focuses on architecting large-scale ML systems, managing production deployments, and promoting best practices across teams. The ideal candidate will have strong experience in AI, deep learning, and modern ML frameworks. Responsibilities include building training pipelines, designing inference systems, and ensuring reliable ML operations. This position is fully remote, offering a chance to work with innovative technologies and contribute to impactful projects.

Posted 4 weeks ago

Primer exists to make the world a safer place. We do this by providing trusted decision-ready AI to the world's most critical organizations. Our software enables leaders, operators, and analysts to better understand the changing world around us in real time and make informed decisions when the stakes are high. Primer has offices in San Francisco, Pasadena, CA and Arlington, VA. For more information, please visit https://primer.ai/ Primer exists to make the world a safer place. We build trusted, decision-ready AI for the organizations that can least afford to be wrong: the leaders, operators, and analysts making high-stakes calls about a world that changes faster than anyone can read it. We have offices in San Francisco, Pasadena, CA, and Arlington, VA. Learn more at primer.ai . The world produces more information every day than any team can read. We build the AI that turns it into a decision you can trust: fast and grounded enough to stake real consequences on. As a Staff Machine Learning Engineer, you’ll own AI-driven products end to end, from the prototype that proves an idea works to the production system the mission depends on. You work fluently across the modern stack: large language models, agentic systems, retrieval, embeddings, fine-tuned models, and the evaluation harnesses that catch them when they drift. You can move fast on an open-ended problem and then harden the result into something reliable at scale, drawing on real distributed-systems experience. You’re energized by what frontier models and agents make newly possible. You reach for them reflexively, including to multiply your own output, and you raise the level of everyone around you as you go. Your technical range matters as much as your judgment about how the pieces fit together. The best work here is designed as part of the whole system, not bolted on beside it, and the engineers with the most impact bring product managers and teammates along with them rather than around them. You’ll partner with product, engineering, and other technical leaders on the hardest version of the problem: putting real AI in the hands of people the moment a decision can’t wait. Role and Responsibilities - How You Will Make an Impact Set both technical and product direction, making the strategic bets across our LLM, agentic, and NLP systems while shaping how we design AI-driven experiences and set expectations with users. Design and build the distributed, agentic systems behind our products at company-wide scale: tool-using conversational agents, multi-turn context, retrieval-grounded reasoning, and the orchestration that ties them together. Turn massive, messy, real-world data into the trustworthy signal agents' reason over: entity recognition and linking, relation extraction, summarization, semantic search, and knowledge-graph generation. Take models from checkpoint to production: package, deploy, and operate low-latency, high-concurrency inference (Triton, vLLM, GPU-backed serving) that stays fast and reliable under real load. Build the evals and labeled-data flywheels that steer the work rather than gate it, turning “it feels better” into proof you can act on. Partner with and influence cross-functional teams to shape the technical roadmap, and drive issues to root cause when quality or operations are on the line. Raise the engineering bar with better patterns, better practices, and a standard other engineers want to match. Relevant Skills and Experience BS, MS, or PhD in computer science, a related field, or equivalent practical experience. 6+ years building production backend software, with a track record of shipping and operating ML-driven functionality. Mastery of data structures and algorithms, and the judgment to translate user needs into practical solutions. Hands-on depth with LLMs and agentic systems (prompt and context engineering, tool use, retrieval and RAG) and the broader ML toolkit such as PyTorch, plus experience defining evals to measure and improve quality. Fluency authoring production APIs in Python (Rust a plus). High agency and a bias to action in ambiguous, fast-moving problems, plus the curiosity, generosity, and love of teaching that lifts a whole team. Bonus Points Experience with knowledge graphs, information retrieval at scale, or LLM fine-tuning and post-training. A pull toward high-stakes, real-world problems where the work actually ships and someone depends on the answer. Primer works closely with the U.S. defense and intelligence establishment. Any offer of employment is conditioned on an applicant or employee being able to meet any applicable government contract requirements. The company may rescind any offer of employment to an applicant or terminate an employee if the applicant or employee is unable to perform the functions of the position in compliance with applicable government contracts or if an applicant or employee makes a false attestation of compliance. What We Offer We are a series D funded company with investors from Addition, USIT, Lux Capital, Amplify Partners, Addition Capital, Bloomberg Beta, and others. W e are intentional around building a diverse and inclusive team of subject matter experts to better advocate for the needs of our users. We care a lot about our work and about the well being of our team. We encourage everyone to work at a sustainable pace and have a flexible vacation policy for team members to utilize, Wellness Days and 100% paid leave for parents of growing families. We offer competitive compensation and comprehensive benefits. This includes full medical, dental, and vision coverage, fertility benefits through Carrot, mental health coverage on demand with Headspace Care+, Gympass+ Membership via Wellhub, One Medical Membership, 401(k), remote work stipends, and monthly internet allowance. Primer is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. Please see the United States Department of Labor's EEO poster and EEO poster supplement for additional information. If you need assistance or accommodation due to a disability, you may contact us at [email protected]. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Posted 2 days ago

About A1 There are over 5 billion users using basic applications today such email, notes, tasks that are not AI-native. Our mission is to build a proactive smart assistant for everyday users to bring intelligence to conversations, errands, organising and workflows, with minimal prompting. Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. The system must handle multi-step reasoning, interact with external tools, and remain reliable despite non-deterministic model behavior. Our objective is to help users complete tasks daily enjoyable with over ~90%* reduced time. Role As Technical Lead, Machine Learning, you own the execution layer of A1’s intelligence. You translate research direction into reliable, scalable, production-grade ML systems. This role sits at the intersection of research, infrastructure, and product. You are responsible for making models trainable, deployable, observable, and performant under real-world constraints. What You'll Do Own end-to-end ML system execution: data pipelines, training workflows, evaluation systems, inference architecture, and deployment. Fine-tune and adapt models using state-of-the-art methods such as LoRA, QLoRA, SFT, DPO, and distillation. Architect and operate scalable inference systems, balancing latency, cost, and reliability. Design and maintain data systems for high-quality synthetic and real-world training data. Implement evaluation pipelines covering performance, robustness, safety, and bias, in partnership with research leadership. Own production deployment, including GPU optimization, memory efficiency, latency reduction, and scaling policies. Collaborate closely with application engineering to integrate ML systems cleanly into backend, mobile, and desktop products. Make pragmatic trade-offs and ship improvements quickly, learning from real usage. Work under real production constraints: latency, cost, reliability, and safety Outcomes Research and models reliably translate into production-ready solutions with clear performance and quality targets. ML pipelines, training loops, and inference systems are stable, efficient, and maintainable. Production issues are detected, debugged, and resolved quickly, minimizing user impact. Team members are supported, aligned, and able to deliver high-impact ML work with minimal friction. Iterations on models and systems are measurable, safe, and improve user experience over time. Tech Stack Python PyTorch / JAX GPU-based training and inference system Ideal Experience You have built or shipped real ML systems used by people, not just demos. You are comfortable working with large models and understanding their failure modes. You write strong, production-grade code and care about system correctness. You are self-directed, pragmatic, and take full ownership of outcomes. You communicate clearly and collaborate well in small, high-trust teams. How We Work The best products today in the world were built by small, world class teams. We are a high talent density and hands-on team. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning. Joining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical product Interview process If there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews. Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite. We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.

Posted 3 days ago

About SailPoint: SailPoint is the leader in identity security for the cloud enterprise. Our identity security solutions secure and enable thousands of companies worldwide, giving our customers unmatched visibility into the entirety of their digital workforce and ensuring that workers have the right access to do their job—no more and no less. Built on a foundation of AI and ML, our Identity Security Cloud Platform delivers the right level of access to the right identities and resources at the right time—matching the scale, velocity, and changing needs of today’s cloud-oriented, modern enterprise. About the Role As a Staff Machine Learning Engineer, you will play a critical role in shaping, building, and scaling SailPoint’s AI-powered capabilities. You’ll work at the intersection of AI innovation, software engineering, and platform architecture—designing robust, production-grade ML systems that deliver customer insights and intelligent automation across our identity platform. As a senior technical leader, you’ll partner closely with engineering, AI, and product teams to drive innovation, define our ML strategy, and mentor others in applying best practices for scalable, responsible AI. This is both a hands-on and strategic role. You will lead complex, end-to-end ML initiatives—from model design and experimentation to deployment, monitoring, and continuous improvement—while advancing the evolution of SailPoint’s AI platform, data pipelines, and model governance standards. About the team: The AI team at SailPoint applies AI and domain expertise to create AI solutions that solve real problems in identity security. We believe the path to success is through meaningful customer outcomes, and we leverage classical ML as well as recent innovations in Generative AI and Graph ML to bring our solutions to SailPoint’s core product lines. Responsibilities Design, implement, and optimize ML models (supervised, unsupervised, and LLM-based) that power both customer-facing and internal product capabilities. Translate AI research and experimental prototypes into scalable, maintainable production systems. Lead technical efforts to improve model accuracy, precision/recall trade-offs, and generalization across diverse regions and customer datasets. Build and enhance ML infrastructure and pipelines for feature extraction, model training, evaluation, deployment, and monitoring. Drive the technical strategy for reproducibility, model versioning, data lineage, and CI/CD automation in ML systems. Collaborate with AI platform and DevOps teams to ensure reliable data access, observability, and efficient use of compute resources. Set technical direction and best practices for ML engineering across the AI organization, influencing architecture and design standards. Mentor and guide engineers in scalable ML design patterns, experimentation frameworks, and software craftsmanship. Partner with product and engineering leaders to prioritize and deliver high-impact AI capabilities aligned with business goals. Work cross-functionally with architecture, platform, and analytics teams to ensure AI components integrate seamlessly across SailPoint’s ecosystem. Advance model lifecycle management, AI governance, and responsible AI practices to ensure quality, fairness, and transparency. Communicate complex ML concepts into actionable insights and recommendations for technical and non-technical audiences. Support day-to-day team operations in partnership with TPMs and managers, ensuring alignment and delivery across initiatives. Requirements: 8+ years of professional experience in machine learning engineering, software development, or a related technical field. Strong programming skills in Python and proficiency with ML frameworks such as PyTorch, TensorFlow, or scikit-learn. Proven track record of building and deploying ML models at production scale (cloud-native environments preferred). Deep understanding of data modeling, feature engineering, and statistical analysis. Expertise in data pipelines, ETL, and feature engineering using frameworks like Spark, Airflow, or dbt. Solid knowledge of MLOps practices—including model monitoring, retraining, CI/CD, and experiment tracking. Strong foundation in software engineering best practices: testing, modularization, code review, and observability. Excellent communication and collaboration skills, with demonstrated experience leading cross-functional technical initiatives. Preferred Experience with LLM-based solutions, embeddings, and retrieval-augmented generation (RAG). Familiarity with identity, security, or enterprise SaaS systems. Experience designing AI platforms or reusable ML services that support multiple product lines. Demonstrated ability to set technical direction, influence architectural decisions, and guide organizational strategy. Roadmap for success- 30 days: Gain deep understanding of SailPoint’s AI vision, architecture, and active ML initiatives. Familiarize with existing data pipelines, environments, and model deployment frameworks. Build relationships with key stakeholders across AI, platform, DevOps, and product teams. Conduct hands-on review of current ML models, data flows, and monitoring systems to identify immediate optimization or reliability gaps. Begin contributing to small improvements or code reviews to gain familiarity with production practices. 90 days: Lead at least one end-to-end ML enhancement or pilot. Establish and document best practices for reproducibility, observability, and CI/CD for ML systems. Mentor junior engineers and support team-wide code quality and experimentation standards. Present a roadmap or proposal for scaling AI components or addressing key technical debt areas. 6 months: Deliver measurable impact on model performance, reliability, or scalability for at least one core AI product. Lead design and implementation of a shared ML service or reusable component (e.g., feature store, inference service, or monitoring framework). Be recognized as a technical go-to for complex ML engineering and architecture decisions. 1 year: Establish SailPoint’s ML engineering foundation as robust, scalable, and production-ready across multiple AI initiatives. Drive one or more flagship AI capabilities from prototype to production, with demonstrated business or customer impact. Mentor and elevate other engineers, fostering a culture of technical excellence and continuous learning. Influence long-term AI platform architecture and strategic investment areas as part of the broader AI leadership group. The Tech Stack (if applicable): Core Programming: SQL, Python, Shell/Bash, Go Cloud Platform: AWS (SageMaker, Bedrock) Data: Snowflake, DBT, Kafka, Airflow, Feast Visualization: Tableau, Qlik CI/CD: Cloudbees, Jenkins Benefits and Compensation listed vary based on the location of your employment and the nature of your employment with SailPoint. As a part of the total compensation package, this role may be eligible for the SailPoint Corporate Bonus Plan or a role-specific commission, along with potential eligibility for equity participation. SailPoint maintains broad salary ranges for its roles to account for variations in knowledge, skills, experience, market conditions and locations, as well as reflect SailPoint’s differing products, industries, and lines of business. Candidates are typically placed into the range based on the preceding factors as well as internal peer equity. We estimate the base salary, for US-based employees, will be in this range from (min-max, USD): $149,200 - $251,576.00 Base salaries for employees based in other locations are competitive for the employee’s home location. Benefits Overview 1. Health and wellness coverage: Medical, dental, and vision insurance 2. Disability coverage: Short-term and long-term disability 3. Life protection: Life insurance and Accidental Death Dismemberment (AD D) 4. Additional life coverage options: Supplemental life insurance for employees, spouses, and children 5. Flexible spending accounts for health care, and dependent care; limited purpose flexible spending account 6. Financial security: 401(k) Savings and Investment Plan with company matching 7. Time off benefits: Flexible vacation policy 8. Holidays: 8 paid holidays annually 9. Sick leave 10. Parental support: Paid parental leave 11. Employee Assistance Program (EAP) and Care Counselors 12. Voluntary benefits: Legal Assistance, Critical Illness, Accident, Hospital Indemnity and Pet Insurance options 13. Health Savings Account (HSA) with employer contribution SailPoint is an equal opportunity employer and we welcome all qualified candidates to apply to join our team. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other category protected by applicable law. Alternative methods of applying for employment are available to individuals unable to submit an application through this site because of a disability. Contact [email protected] or mail to 11120 Four Points Dr, Suite 100, Austin, TX 78726, to discuss reasonable accommodations. NOTE: Any unsolicited resumes sent by candidates or agencies to this email will not be considered for current openings at SailPoint.

Posted 1 week ago

TriumphPay is seeking a Staff Machine Learning Engineer to join a dedicated team focused on building innovative AI/ML systems for the transportation payments network of the future. In this role, you'll collaborate in a small, autonomous team to deliver impactful solutions, manage complex data processing, and ensure alignment with customer needs. The position emphasizes work-life balance in a fully remote environment, requiring strong software development skills and a passion for continuous learning.

Posted 1 week ago

Grailed seeks a Staff Machine Learning Engineer to develop models that enhance user experience in a peer-to-peer marketplace. This hands-on role requires end-to-end ownership, focusing on model accuracy and system reliability. Candidates should have substantial experience with production ML systems and a keen understanding of e-commerce contexts. Responsibilities include lifecycle management of predictive models and collaborative work across teams to drive production system solutions.

Posted 2 weeks ago

GOAT Group is seeking a Staff Machine Learning Engineer to enhance the connection between buyers and inventory in its peer-to-peer marketplace. This role involves full lifecycle management of predictive models, from architecture to deployment, and requires a hands-on engineer with production instincts. Candidates should possess advanced knowledge in machine learning, along with strong Python and SQL skills. The position emphasizes collaboration within a small team, fostering an environment for innovation in a rapidly growing company focused on e-commerce.

Posted 2 weeks ago

Join Xero as a Staff Machine Learning Engineer to design, build, and deploy backend generative AI solutions for automated workflows. You will tackle complex R&D challenges to create production-ready software while owning the machine learning architecture. Work with a collaborative AI team across Canada and the US, focusing on cutting-edge Agentic AI implementations. This fully remote role allows for flexibility in working hours, primarily connecting through virtual meetings. Candidates should have strong backend engineering skills and a passion for AI tools.

Posted 2 weeks ago