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Junior Machine Learning Remote Jobs (NOW HIRING)

Rockstar

Jr AI Engineer

Position Summary Our client is seeking a Jr. AI Engineer/Jr. Machine Learning Engineer to support the development, testing, and improvement of AI-powered features across their data intelligence ...

Alignerr

Machine Learning Engineer

Manhattan, NY · Remote

$50 - $70/hr

Remote About The Job At Alignerr, we partner with the world's leading AI research teams and labs to ... Machine Learning Engineer - AI Data Trainer Type: Hourly Contract Compensation: $50-$70 /hour ...

Compunnel

Machine Learning Engineer

Freeport, ME · Remote

Freeport Maine Remote Must haves: 4+ years ML experience Python / Spark Tensorflow / PyTorch (or similar) Databricks MLflow Docker SQL Design and implement machine learning models and algorithms ...

Alignerr

Machine Learning Engineer What if your technical expertise could directly influence how the world ... This is a fully remote, flexible contract role built for experienced technical professionals who ...

Pluralsight LLC

Machine Learning Engineer

$121.60K - $160K/yr

A Machine Learning Engineer helps our learners discover content that is relevant to their interests ... This is a remote role; however, applicants located within 45 miles of our Westlake/Dallas, TX ...

Avride

Machine Learning Engineer

Austin, TX · On-site +1

Machine Learning Engineer Austin, TX About the Team Avride develops autonomous vehicle and delivery ... The employer is not offering relocation sponsorship, and remote work options are not available.

Strayos

$13 - $17.50/hr

As an intern, you will learn how to implement novel, cutting-edge remote sensing and machine learning techniques to solve challenging research questions. To efficiently execute your solutions, you ...

PTP

Machine Learning Engineer - REMOTE

Austin, TX · On-site +1

We are looking for a Machine Learning Engineer to help us design and deliver CX solutions that provide our clients with a beautiful customer journey that achieves results. At PTP we value aptitude ...

NSS

Machine Learning Engineer

Concord, NC · Remote

Together with a small machine learning team, you will be responsible to ensure the successful ... Remote-first environment (if that's your thing) * Dedicated collaborative office space in NoVA (if ...

NSS

Machine Learning Engineer

Concord, NC · Remote

Together with a small machine learning team, you will be responsible to ensure the successful ... Remote-first environment (if that's your thing) * Dedicated collaborative office space in NoVA (if ...

Wings of Destiny

Machine Learning Engineer

Malibu, CA · Remote

Remote Commitment: 5-10 hours per week (flexible) Duration: 3-6 months (with potential extension ... Role Overview We are seeking a Machine Learning Engineer (Volunteer) to help design, build, and ...

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Junior Machine Learning Remote information

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$46.5K

$94.5K

$142K

How much do junior machine learning remote jobs pay per year?

As of May 28, 2026, the average yearly pay for junior machine learning remote in the United States is $94,542.00, according to ZipRecruiter salary data. Most workers in this role earn between $73,000.00 and $95,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Junior Machine Learning Engineer (Remote), and why are they important?

To thrive as a Junior Machine Learning Engineer (Remote), you need a solid understanding of programming (especially Python), statistics, and foundational machine learning concepts, typically supported by a relevant degree or coursework. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is highly valued. Strong problem-solving abilities, effective communication, and self-motivation are important soft skills for remote collaboration and continuous learning. These skills and qualities are crucial for successfully building, deploying, and improving machine learning models while working efficiently in a distributed team environment.

What are some common challenges faced by Junior Machine Learning Engineers working remotely, and how can they be addressed?

Junior Machine Learning Engineers working remotely often face challenges like limited access to mentorship, difficulty in collaborating on code or data projects, and staying updated with rapidly evolving tools. To address these, it's helpful to proactively seek regular check-ins with teammates, participate in virtual code reviews, and make use of collaborative platforms such as GitHub and Slack. Additionally, engaging in online communities and continuous learning through webinars or courses can help bridge knowledge gaps and foster professional growth.

What does a Junior Machine Learning Engineer do when working remotely?

A Junior Machine Learning Engineer working remotely assists in developing, testing, and deploying machine learning models under the guidance of more experienced engineers. Their tasks often include data cleaning, feature engineering, writing code for model training, and helping with basic evaluations of model performance. They collaborate with team members virtually, participate in code reviews, and may also help document processes or results. Remote work requires good communication skills, self-motivation, and a solid understanding of basic machine learning concepts and tools.
What are the most commonly searched types of Machine Learning Remote jobs? The most popular types of Machine Learning Remote jobs are:
Infographic showing various Junior Machine Learning Remote job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 64% Full Time, 30% Part Time, 1% Temporary, 2% Contract, and 2% Nights. Highlights an 67% Physical, 6% Hybrid, and 27% Remote job distribution, with an average salary of $94,542 per year, or $45.5 per hour.
Jr AI Engineer

Jr AI Engineer

Rockstar

Remote

Full-time

Posted 8 days ago

Job description

Rockstar is recruiting for a data intelligence platform company focused on security analytics, investigations, fraud detection, and enterprise AI systems. Their team is dedicated to building production AI products that help organizations extract actionable insights from complex data. They are seeking a Jr. AI Engineer to contribute to their growing AI capabilities.
Position Summary
Our client is seeking a Jr. AI Engineer/Jr. Machine Learning Engineer to support the development, testing, and improvement of AI-powered features across their data intelligence platform. This role is designed for an early-career engineer who has strong technical fundamentals, curiosity about GenAI systems, and an interest in learning how production AI products are built and maintained.
The Jr. AI Engineer will work closely with senior engineers to assist with prompt experimentation, data preparation, RAG pipeline support, model evaluation, documentation, debugging, and basic AI service development. This role offers hands-on exposure to LLMs, embeddings, retrieval systems, ML workflows, and production engineering practices.
Essential Responsibilities
  • Assist in developing AI-powered features using Python, LLM tools, ML libraries, APIs, and internal platform services.
  • Support prompt engineering, prompt testing, model comparison, and evaluation of AI-generated outputs.
  • Help build and maintain RAG workflows, including document preparation, chunking, metadata tagging, embedding generation, retrieval testing, and result review.
  • Prepare, clean, format, and validate datasets used for model testing, prompt evaluation, and AI experiments.
  • Assist with model and workflow evaluation by reviewing outputs, identifying errors, documenting patterns, and comparing performance across approaches.
  • Write clean, readable Python code for scripts, internal tools, prototypes, experiments, and service components.
  • Support debugging of AI workflows, data pipelines, API integrations, and model behavior under the guidance of senior engineers.
  • Participate in code reviews, design discussions, team planning, and documentation efforts.
  • Learn and apply production engineering practices, including Git workflows, testing, logging, Docker, CI/CD, and deployment basics.
  • Document experiments, implementation details, findings, and recommendations clearly for technical team members.

Required Qualifications
  • 0-2 years of experience in AI engineering, machine learning, software engineering, data science, or a related technical area.
  • Internship experience, academic work, bootcamp projects, portfolio projects, or open-source contributions are acceptable.
  • Solid Python programming skills.
  • Foundational understanding of machine learning, deep learning, NLP, data processing, and model evaluation concepts.
  • Familiarity with tools or libraries such as PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers, pandas, NumPy, or similar technologies.
  • Interest in LLMs, GenAI systems, prompt engineering, embeddings, semantic search, RAG, and AI agents.
  • Ability to work with structured and unstructured data.
  • Comfort using Git, notebooks, command-line tools, APIs, and collaborative development workflows.
  • Strong attention to detail, curiosity, problem-solving ability, and willingness to learn from feedback.
  • Clear written communication skills for documenting technical work and experiment results.

Preferred Qualifications
  • Portfolio, academic, internship, or project experience involving LLMs, chatbots, semantic search, classification, summarization, automation, or ML workflows.
  • Exposure to vector databases, embeddings, document processing, information retrieval, or search systems.
  • Familiarity with Docker, cloud environments, CI/CD concepts, or basic deployment workflows.
  • Exposure to agent frameworks such as LangGraph, AutoGen, CrewAI, or similar tools.
  • Coursework or practical experience in machine learning, NLP, statistics, data engineering, computer science, or software engineering.
  • Interest in security analytics, investigations, data intelligence, fraud detection, or enterprise AI systems.

Special Skills or Experience Required
  • Foundational knowledge of machine learning, deep learning, NLP, LLMs, prompt engineering, and RAG concepts.
  • Solid Python skills with exposure to ML libraries such as PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers, or similar tools.
  • Experience through coursework, internships, projects, or portfolio work involving AI, data preparation, model testing, search, or automation.
  • Ability to document experiments, compare model outputs, support debugging, and learn production ML practices such as Git, APIs, Docker, and CI/CD.

Success Measures
Success in this role will be measured by consistent contribution to AI experiments, clean and reliable implementation work, clear documentation, improved evaluation support, effective debugging assistance, and steady growth in production AI engineering skills. The role should help increase team capacity while developing strong internal AI engineering talent over time.

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