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Junior Machine Learning Jobs in Virginia (NOW HIRING)

Junior Data Scientist

Arlington, VA · On-site

$100K - $120K/yr

Junior Data Scientist / Performance Data Analyst I Location: Washington, DC / Hybrid / Government ... Experience with machine learning classification, NLP, model evaluation, or predictive analytics.

Junior Data Scientist

Arlington, VA · On-site

$100K - $120K/yr

Junior Data Scientist / Performance Data Analyst I Location: Washington, DC / Hybrid / Government ... Experience with machine learning classification, NLP, model evaluation, or predictive analytics.

Everforth ECS is seeking a Junior Software Engineer Intern to work in our Fairfax, VA office for ... Machine Learning and Big Data/Cloud Solutions. The candidate works closely with the Project Manager ...

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Junior Machine Learning information

See Virginia salary details

$7

$26

$46

How much do junior machine learning jobs pay per hour?

As of May 29, 2026, the average hourly pay for junior machine learning in Virginia is $26.73, according to ZipRecruiter salary data. Most workers in this role earn between $16.20 and $32.88 per hour, depending on experience, location, and employer.

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

To thrive as a Junior Machine Learning Engineer, you need a solid understanding of programming (especially Python), basic statistics, linear algebra, and familiarity with machine learning concepts, typically supported by a relevant degree or coursework. Proficiency in tools and frameworks like scikit-learn, TensorFlow, PyTorch, and version control systems such as Git is often expected. Strong problem-solving abilities, curiosity, and effective communication are crucial soft skills for collaborating with teams and explaining technical concepts. These skills and qualities are important because they enable you to contribute effectively to building, testing, and improving machine learning models in real-world applications.

What types of projects and tasks can a Junior Machine Learning professional typically expect to work on in their first year?

As a Junior Machine Learning professional, you’ll often support senior data scientists and engineers by preparing data, implementing basic algorithms, and assisting with model evaluation. Your daily tasks may include data cleaning, feature engineering, running experiments, and writing code to automate data pipelines. You might also help document processes and present your findings to team members. While the work is often collaborative, you’ll have opportunities to take ownership of smaller projects and progressively contribute to larger initiatives as you gain experience.

What does a Junior Machine Learning Engineer do?

A Junior Machine Learning Engineer assists in the development and implementation of machine learning models and algorithms under the supervision of more experienced engineers. They typically help with data collection, cleaning, feature engineering, model training, and evaluation. Junior engineers may also write code, test prototypes, and contribute to improving model performance while learning best practices in the field. Their role often involves collaborating with data scientists and software engineers to integrate machine learning solutions into products or services.

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

AspectJunior Machine LearningData Scientist
Required CredentialsBachelor's in CS, Data Science, or related field; some experience with ML toolsBachelor's or Master's in CS, Statistics, or related; strong programming and statistical skills
Work EnvironmentEntry-level projects, supervised tasks, team collaborationAdvanced analysis, model development, cross-functional teams
Industry UsageCommon in tech companies, startups, research labsWidespread across industries like finance, healthcare, tech

Junior Machine Learning roles focus on foundational ML tasks and learning on the job, while Data Scientists handle complex data analysis, model building, and strategic insights. The roles differ mainly in experience level and scope of responsibilities, but both require strong technical skills and familiarity with data tools.

What are the most commonly searched types of Machine Learning jobs in Virginia? The most popular types of Machine Learning jobs in Virginia are:
What cities in Virginia are hiring for Junior Machine Learning jobs? Cities in Virginia with the most Junior Machine Learning job openings:
Lead Machine Learning / Data Science Engineer

Lead Machine Learning / Data Science Engineer

CapTech Consulting

Richmond, VA • On-site

$55.25 - $73/hr

Full-time

Medical, Retirement, PTO

Posted 26 days ago


Job description

Company Description

CapTech is an award-winning consulting firm that collaborates with clients to achieve what's possible through the power of technology. At CapTech, we're passionate about the work we do and the results we achieve for our clients. From the outset, our founders shared a collective passion to create a consultancy centered on strong relationships that would stand the test of time. Today we work alongside clients that include Fortune 100 companies, mid-sized enterprises, and government agencies, a list that spans across the country.

Job Description

CapTech Machine Learning Engineers are responsible for designing and implementing data-driven solutions for our clients, with a specific focus on building and deploying scalable machine learning systems in enterprise environments. CapTech employees enjoy a collaborative environment and have many opportunities to learn from and share knowledge with other CapTech analysts, architects, and our clients.

Specific responsibilities for the Lead Machine Learning Engineer position include:

  • Strategizing with clients, data scientists, engineers, and other members of cross-functional teams to implement end-to-end machine learning solutions and identify new machine learning and data science approaches to meet business needs
  • Provide technical leadership and collaborate within and across teams to ensure that the overall technical solution is aligned with the customer needs. 
  • Deconstructing client needs into data-driven processes/models and analytical measures.
  • Analyzing and transforming large datasets hosted on a variety of enterprise-level data platforms (e.g., AWS, Azure, GCP).
  • Designing, developing, and deploying advanced analytical solutions leveraging client data (e.g., recommender systems, natural language processing, risk scoring).
  • Productionizing ML systems with a focus on optimization and scalability to satisfy clients' requirements.
  • Growing CapTech's Machine Learning and Data Science practices through delivering client presentations, writing proposals, attending various business development events, and leading teams of junior data scientists and engineers.
Qualifications
  • 7+ years of experiencedelivering data engineering and machine learning solutionson cloudplatforms 
  • Bachelor's degree or equivalent combination of education and experience.
  • Experience providing technical leadership and mentoring other engineers in data engineering space 
  • Hands-on experience manipulating and analyzing large (multi-billion record) data sets.
  • Hands-on experience developing data-driven solutions using Python, Scala, or similar languages.
  • Proficiency leveraging SQL, Spark, NoSQL, and/or cloud data processing frameworks in a production setting.
  • Proficiency with containerization (e.g., Docker) and microservices.
  • Proficiency with data warehousing tools/environments such as Snowflake, Databricks, Azure SQL, Amazon RDS
  • Comfort and proficiency in framing data-driven problems from cross-industry business requirements.
  • Experience applying analytical methods across multiple business domains (e.g., customer analytics, marketing, finance, digital channels)
  • Hands-on experience implementing production-scale machine learning systems in one or more domains (i.e., personalization, natural language processing, computer vision).
  • Knowledge of DevOps and automation best practices.
  • Knowledge of statistics and statistical modeling methods.
  • Knowledge of model management and model versioning best practices.
  • Experience working with LLMs (e.g., GPT, Claude, Mistral, etc.) in production setting 
  • Experience with prompt engineering, MCP and RAG, and agentic AI architectures 
  • Strong understanding of conversational UX and prompt evaluation metrics 
  • Experience with agentic frameworks in practice (langchain, n8n, pydantic, etc.)
  • Experience with multi-agent orchestration
Additional Information

We want everyone at CapTech to be able to envision a lasting and rewarding career here, which is why we offer a variety of career paths based on your skills and passions.  You decide where and how you want to develop, and we help get you there with customizable career progression and a comprehensive benefits package to support you along the way.  Alongside our suite of traditional benefits encompassing generous PTO, health coverage, disability insurance, paid family leave and more, we've launched extended benefits to help meet our employees' needs. 

  • CapTech is committed to providing a flexible work environment and helping our employees achieve a work-life balance that suits their individual needs. Employees must be available to work onsite in a client location or a CapTech office as requested. We allow CapTech employees to work remotely when compatible with CapTech and client needs. 
  • Learning & Development - Programs offering certification and tuition support, digital on-demand learning courses, mentorship, and skill development paths
  • Modern Health -A mental health and well-being platform that provides 1:1 care, group support sessions, and self-serve resources to support employees and their families through life's ups and downs
  • Carrot Fertility -Inclusive fertility and family-forming coverage for all paths to parenthood - including adoption, surrogacy, fertility treatments, pregnancy, and more - and opportunities for employer-sponsored funds to help pay for care
  • Fringe -A company paid stipend program for personalized lifestyle benefits, allowing employees to choose benefits that matter most to them - ranging from vendors like Netflix, Spotify, and GrubHub to services like student loan repayment, travel, fitness, and more
  • Employee Resource Groups - Employee-led committees that embrace and incorporate diversity and inclusion into our day-to-day operations
  • Philanthropic Partnerships - Opportunities to engage in partnerships and pro-bono projects that support our communities. 
  • 401(k) Matching - Generous matching and no vesting period to help you continue to build financial wellness

CapTech is an equal opportunity employer committed to fostering a culture of equality, inclusion and fairness - each foundational to our core values.  We strive to create a diverse environment where each employee is encouraged to bring their unique ideas, backgrounds and experiences to the workplace. For more information about our Diversity, Inclusion and Belonging efforts, click HERE.  As part of this commitment, CapTech will ensure that persons with disabilities are provided reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact Laura Massa directly via email [email protected].

At this time, CapTech cannot transfer nor sponsor a work visa for this position. Applicants must be authorized to work directly for any employer in the United States without visa sponsorship.