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Junior Machine Learning Engineer Jobs (NOW HIRING)

SynergisticIT

Machine Learning Engineer

Rolla, MO

Machine Learning Engineer Opportunity SynergisticIT understands the complex nature of the job ... Junior or entry-level position each additional Technical skill helps a candidate's resume to be ...

ExtendMyTeam

Machine Learning Engineer

Cary, NC

Position Summary We are seeking a Machine Learning Engineer to help design, deploy, and support production machine learning systems within a collaborative engineering organization. This individual ...

NTENT

Machine Learning Engineer

Carlsbad, CA · On-site

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

Purple Drive

Machine Learning Engineer

Newark, NJ

Machine Learning Engineer As a Machine Learning Engineer , you will play a critical role in designing, developing, and deploying advanced machine learning solutions that drive innovation and create ...

Alignerr

Machine Learning Engineer

Denver, CO · Remote

$50 - $70/hr

Machine Learning Engineer - AI Data Trainer * Location: Remote About the job At Alignerr, we partner with the world's leading AI research teams and labs to build and train cutting-edge AI models.

NTENT

Machine Learning Engineer

Carlsbad, CA

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

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Junior Machine Learning Engineer information

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

As of Jun 3, 2026, the average yearly pay for junior machine learning engineer in the United States is $71,799.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,500.00 and $80,000.00 per year, depending on experience, location, and employer.

What Does a Junior Machine Learning Engineer Do?

As a junior machine learning engineer, you work in AI, performing research with algorithms and data modeling techniques. Machine learning involves using large collections of data to create systems that are capable of making predictions, and in this field, your duties and responsibilities revolve around using advanced mathematics to design applications for use in everything from stock trading to sports betting. Some machine learning efforts involve images, and this branch of the field is known as computer vision, while other techniques which focus on text are called natural language processing (NLP). Given these divisions, titles in machine learning include computer vision engineer, NLP scientist, or simply research scientist.

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

To succeed as a Junior Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of algorithms and statistics, and a relevant degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch and tools like scikit-learn, as well as experience with version control systems like Git, are typically required. Strong problem-solving abilities, attention to detail, and a willingness to learn from feedback are valuable soft skills that help you adapt and grow in the field. These skills ensure you can effectively develop, test, and improve machine learning models while collaborating with more experienced engineers and contributing to team projects.

What kinds of projects and responsibilities can a Junior Machine Learning Engineer expect in their first year on the job?

As a Junior Machine Learning Engineer, you’ll typically work on tasks such as data preprocessing, building and testing simple models, and supporting more senior engineers in deploying machine learning solutions. Your responsibilities may also include cleaning datasets, implementing basic algorithms, and running experiments to evaluate model performance. You’ll often collaborate closely with data scientists, software engineers, and product teams to understand project goals and learn best practices. The role provides excellent opportunities to develop your technical skills, gain exposure to various stages of the ML pipeline, and gradually take on more complex projects as you grow.

What is the difference between Junior Machine Learning Engineer vs Data Scientist?

AspectJunior Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; some experience with ML frameworksBachelor's or higher in CS, Statistics, or related; often advanced certifications
Work EnvironmentDeveloping and deploying ML models, coding, testingData analysis, statistical modeling, interpreting data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, tech, consulting
Search & Comparison IntentYesYes

While both roles involve working with data and machine learning, Junior Machine Learning Engineers focus on building and deploying models, often with coding and engineering skills. Data Scientists analyze data, create statistical models, and interpret insights. The roles overlap but differ mainly in their core responsibilities and skill emphasis.

More about Junior Machine Learning Engineer jobs
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What job categories do people searching Junior Machine Learning Engineer jobs look for? The top searched job categories for Junior Machine Learning Engineer jobs are:
Junior Machine Learning Engineer jobs near you
Machine Learning Engineer

Machine Learning Engineer

Samprasoft

Roanoke, TX

Other

Posted 22 days ago

Job description

Sr. Machine Learning Engineer

Duration: 12 -24 Months

Location: Merrimack, NH/ Smithfield, RI/ Westlake, TX/ Durham, NC/ Covington, KY/ Jersey City, NJ/ Boston, MA

Candidate should be local or willing to work onsite on any of the above locations for 5 days/ month

The Expertise And Skills You Bring
  • Bachelor’s or Master’s Degree in a technology related field (e.g. Engineering, Computer Science, etc.)
  • 8+ years of proven experience in implementing Big data solutions in data analytics space
  • 2+ years of experience in developing ML infrastructure and MLOps in the Cloud using AWS Sagemaker
  • Extensive experience working with machine learning models with respect to deployment, inference, tuning, and measurement required
  • Experience in Object Oriented Programming (Java, Scala, Python), SQL, Unix scripting or related programming languages and exposure to some of Python’s ML ecosystem (numpy, panda, sklearn, tensorflow, etc.)
  • Experience with building data pipelines in getting the data required to build and evaluate ML models, using tools like Apache Spark or other distributed data processing frameworks
  • Data movement technologies (ETL/ELT), Messaging/Streaming Technologies (AWS SQS, Kinesis/Kafka), Relational and NoSQL databases (DynamoDB, EKS, Graph database), API and in-memory technologies
  • Strong knowledge of developing highly scalable distributed systems using Open-source technologies
  • Experience with CI/CD tools (e.g., Jenkins or equivalent), version control (Git), orchestration/DAGs tools (AWS Step Functions, Airflow, Luigi, Kubeflow, or equivalent)
  • Solid experience in Agile methodologies (Kanban and SCRUM)
  • Strong technical design and analysis skills
  • Ability to deal with ambiguity and work in fast paced environment
  • Experience supporting critical applications
  • Familiarity with applied data science methods, feature engineering and machine learning algorithms
  • Data wrangling experience with structured, semi-structured and unstructured data
  • Experience building ML infrastructure, with an eye towards software engineering
  • Excellent communication skills, both through written and verbal channels
  • Excellent collaboration skills to work with multiple teams in the organization
  • Ability to understand and adapt to changing business priorities and technology advancements in Big data and Data Science ecosystem

Required Skills : Basic Qualification : Additional Skills : Please do not send junior candidates, Need 10 plus years of experience.

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