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Junior Ai Machine Learning Python Jobs in Richmond, VA

... Python Integrate AI agents with enterprise tools, APIs, and workflows Evaluate, monitor, and ... machine learning, AI engineering, or applied ML Strong proficiency in Python for ML and backend ...

Machine Learning with Python Development

Richmond, VA · On-site

$49.75 - $68.75/hr

Good Machine Learning foundations, practical experience with classification, regression and clustering methods strong python coding, computing fundamentals/data structures, SQL, experience with ...

Sr. Engineer, AI & ML

Richmond, VA · On-site

$103K - $142K/yr

... AI system. As a member of the GenAI team , you will have a direct impact on improving the ... Familiarity with MLOps and industry-standard machine-learning Python libraries * Enthusiastic about ...

Sr. Engineer, AI & ML

Richmond, VA · On-site

$103K - $142K/yr

... AI system. As a member of the GenAI team, you will have a direct impact on improving the ... Familiarity with MLOps and industry-standard machine-learning Python libraries * Enthusiastic about ...

Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ... Adapts instruction using Python with scikit-learn, Jupyter notebooks, and real-world data sets to ...

AI Engineer

Manakin Sabot, VA · On-site

$152K/yr

Design, develop, and implement AI and machine learning models for a variety of business ... Provide technical guidance and support to junior team members, helping them grow their skills in AI ...

AI Engineer

VA · On-site

$152K/yr

Design, develop, and implement AI and machine learning models for a variety of business ... Provide technical guidance and support to junior team members, helping them grow their skills in AI ...

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Junior Ai Machine Learning Python information

See Richmond, VA salary details

$46K

$93.6K

$140.5K

How much do junior ai machine learning python jobs pay per year?

As of Aug 7, 2026, the average yearly pay for junior ai machine learning python in Richmond, VA is $93,562.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,200.00 and $94,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a junior AI machine learning Python engineer, and why are they important?

To thrive as a Junior AI Machine Learning Python Engineer, you need a solid understanding of Python programming, statistics, and foundational machine learning concepts, often supported by a degree in computer science or a related field. Familiarity with tools and frameworks like TensorFlow, Scikit-learn, Jupyter Notebooks, and version control systems such as Git is typically required. Strong problem-solving abilities, attention to detail, and effective teamwork skills help individuals excel in collaborative and fast-evolving technical environments. These competencies are crucial for developing robust AI solutions, learning from senior colleagues, and adapting to the rapidly changing landscape of machine learning.

What does a junior AI machine learning Python engineer do?

A Junior AI Machine Learning Python engineer assists in developing, testing, and maintaining machine learning models using Python. They typically work with data preparation, preprocessing, and applying basic algorithms to solve real-world problems. Under the guidance of senior engineers, they help implement solutions, evaluate model performance, and may contribute to the deployment of models into production environments. Their role often includes learning best practices in coding, software development, and collaborating with data scientists and engineers.

What are some typical projects or tasks a junior AI machine learning Python developer might work on in their first year?

As a Junior AI/Machine Learning Python developer, you can expect to work on tasks such as cleaning and preparing datasets, developing and testing simple machine learning models, and assisting in the implementation of algorithms under the supervision of senior team members. You may also help automate data pipelines, write scripts for data extraction, and contribute to model evaluation and reporting. Collaboration with data scientists, software engineers, and product managers is common, providing valuable learning opportunities and exposure to the full machine learning workflow.

What is the difference between Junior Ai Machine Learning Python vs Data Analyst?

AspectJunior Ai Machine Learning PythonData Analyst
Required SkillsPython, Machine Learning, AI concepts, data preprocessingExcel, SQL, data visualization, basic statistical analysis
CertificationsPython certifications, AI/ML coursesData analysis or visualization certifications
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, marketing departments
Industry UsageDeveloping AI models, machine learning pipelinesInterpreting data, generating reports, supporting decision-making

Junior Ai Machine Learning Python roles focus on developing AI models using Python and machine learning techniques, often in tech-driven environments. Data Analysts primarily interpret data, create visualizations, and support business decisions. While both roles require analytical skills, AI/ML roles demand programming and AI-specific knowledge, whereas Data Analysts focus on data interpretation and reporting.

What are popular job titles related to Junior Ai Machine Learning Python jobs in Richmond, VA? For Junior Ai Machine Learning Python jobs in Richmond, VA, the most frequently searched job titles are:
What job categories do people searching Junior Ai Machine Learning Python jobs in Richmond, VA look for? The top searched job categories for Junior Ai Machine Learning Python jobs in Richmond, VA are:
What cities near Richmond, VA are hiring for Junior Ai Machine Learning Python jobs? Cities near Richmond, VA with the most Junior Ai Machine Learning Python job openings:
Infographic showing various Junior Ai Machine Learning Python job openings in Richmond, VA as of June 2026, with employment types broken down into 67% Full Time, 21% Part Time, 3% Temporary, 6% Contract, and 3% Nights. Highlights an 69% Physical, 3% Hybrid, and 28% Remote job distribution, with an average salary of $93,562 per year, or $45 per hour.

Machine Learning Engineer

WorkNovas LLC

Richmond, VA • On-site

Contractor

Re-posted 16 days ago


Job description

Machine Learning Engineer  

Richmond, Virginia (5 Days Onsite) need local within commute

About the Role
We are seeking a Machine Learning Engineer with expertise in agentic AI systems to design, build, and deploy next-generation AI solutions. In this role, you will work at the intersection of LLMs, autonomous agents, retrieval-augmented generation (RAG), and enterprise-scale systems, leveraging Azure AI Foundry, Copilot Studio, and modern orchestration frameworks.
You will collaborate closely with product managers, architects, and application teams to deliver intelligent, production-grade AI agents that integrate seamlessly with business workflows and enterprise data.
Key Responsibilities
Design and implement agentic AI systems capable of planning, tool use, memory, and multi-step reasoning
Build and deploy AI solutions using Azure AI Foundry and Copilot Studio
Develop RAG pipelines integrating structured and unstructured enterprise data
Implement and optimize vector databases for semantic search and long-term agent memory
Orchestrate LLM-based agents using frameworks such as LangChain (or equivalent)
Develop scalable backend services and APIs using Python
Integrate AI agents with enterprise tools, APIs, and workflows
Evaluate, monitor, and optimize agent performance, reliability, and cost
Apply responsible AI principles including security, privacy, and governance
Stay current with advancements in LLMs, agent architectures, and Azure AI services
Required Qualifications
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
5+ years of experience in machine learning, AI engineering, or applied ML
Strong proficiency in Python for ML and backend development
Hands-on experience building LLM-based applications
Practical experience with agentic AI patterns (tool calling, planning, memory, reflection)
Experience with LangChain or similar agent orchestration frameworks
Solid understanding of RAG architectures
Experience with vector databases (e.g., Azure AI Search, Pinecone, etc.)
Familiarity with Azure cloud services and enterprise-grade deployments
Hands-on experience with MCP and/or A2A agent communication frameworks
Preferred Qualifications
Direct experience with Azure AI Foundry and Copilot Studio
Experience integrating AI agents into enterprise workflows or SaaS platforms
Knowledge of prompt engineering, evaluation frameworks, and guardrails
Experience with CI/CD, MLOps, or AI observability
Understanding of security, identity, and compliance in enterprise AI systems
Nice-to-Have
Contributions to AI prototypes, internal platforms, or open-source projects
Experience moving AI solutions from prototype to production
Strong communication skills and ability to explain complex AI systems to non-experts