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Python Ml Developer Jobs in Silver Spring, MD (NOW HIRING)

VXForward

AI/ML Engineer

Washington, DC · Remote

Collaborate with DevOps and infrastructure teams to ensure secure, scalable deployment and ... in Python, Golang, JavaScript, or Java * 3+ years of hands-on experience with AI/ML frameworks ...

VXForward

AI/ML Engineer

Washington, DC · Remote

Collaborate with DevOps and infrastructure teams to ensure secure, scalable deployment and ... in Python, Golang, JavaScript, or Java * 3+ years of hands-on experience with AI/ML frameworks ...

VXForward

AI/ML Engineer

Washington, DC · Remote

Collaborate with DevOps and infrastructure teams to ensure secure, scalable deployment and ... in Python, Golang, JavaScript, or Java * 3+ years of hands-on experience with AI/ML frameworks ...

Mindlance

Senior Python Developer

Mclean, VA

$124K - $167K/yr

Strong Python Developer with strong experience in Python development, SQL, and database ... Java proficiency (preferred) , particularly for AI/ML development and automation. Soft Skills:

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All JobsPython Ml Developer JobsPython Ml Developer Jobs in Silver Spring, MD

Python Ml Developer information

See Silver Spring, MD salary details

$13

$60

$89

How much do python ml developer jobs pay per hour?

As of Jun 21, 2026, the average hourly pay for python ml developer in Silver Spring, MD is $60.60, according to ZipRecruiter salary data. Most workers in this role earn between $49.95 and $68.85 per hour, depending on experience, location, and employer.

What does a Python ML Developer do?

A Python ML Developer designs, builds, and deploys machine learning models using the Python programming language. They work with large datasets, clean and process data, select appropriate algorithms, and use libraries like TensorFlow, PyTorch, or scikit-learn to implement solutions. Their work often involves collaborating with data scientists and engineers to integrate machine learning models into applications. Additionally, they may be responsible for testing, tuning, and optimizing models to achieve the best possible performance in real-world scenarios.

What are some common challenges Python ML Developers face when deploying machine learning models to production?

Python ML Developers often encounter challenges such as ensuring model scalability, managing dependencies, and maintaining reproducibility when deploying models into production environments. Integrating machine learning models with existing systems can require close collaboration with DevOps and software engineering teams to streamline workflows and automate deployment pipelines. Additionally, monitoring model performance over time and handling data drift are crucial responsibilities to ensure continued accuracy and reliability of deployed solutions.

What are the key skills and qualifications needed to thrive as a Python ML Developer, and why are they important?

To thrive as a Python ML Developer, you need strong programming skills in Python, a solid understanding of machine learning algorithms, and a background in mathematics or statistics, often supported by a degree in computer science, engineering, or a related field. Familiarity with tools and libraries such as TensorFlow, scikit-learn, PyTorch, and version control systems like Git is essential, along with experience using data visualization and cloud platforms. Critical soft skills include problem-solving, adaptability, and effective communication to collaborate with cross-functional teams and explain complex models to stakeholders. These skills ensure the successful development, deployment, and maintenance of machine learning solutions that drive business value.

What is the difference between Python Ml Developer vs Data Scientist?

AspectPython Ml DeveloperData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; Python, ML certificationsBachelor's/Master's in Data Science, Statistics, or related; Python, ML certifications
Work EnvironmentSoftware development teams, AI/ML projectsResearch, data analysis, modeling teams
Employer & Industry UsageTech companies, startups, AI firmsFinance, healthcare, tech, research institutions
Common Search & ComparisonYesYes

Python ML Developers focus on building and deploying machine learning models using Python, often working closely with software engineering teams. Data Scientists analyze data, create models, and generate insights, often using Python along with statistical tools. While both roles require Python and ML knowledge, Python ML Developers are more involved in implementation and deployment, whereas Data Scientists focus on data analysis and research.

What are popular job titles related to Python Ml Developer jobs in Silver Spring, MD? For Python Ml Developer jobs in Silver Spring, MD, the most frequently searched job titles are:
What job categories do people searching Python Ml Developer jobs in Silver Spring, MD look for? The top searched job categories for Python Ml Developer jobs in Silver Spring, MD are:
What cities near Silver Spring, MD are hiring for Python Ml Developer jobs? Cities near Silver Spring, MD with the most Python Ml Developer job openings:
Python Ml Developer jobs near you
Infographic showing various Python Ml Developer job openings in Silver Spring, MD as of June 2026, with employment types broken down into 93% Full Time, 5% Part Time, and 2% Contract. Highlights an 83% Physical, 5% Hybrid, and 12% Remote job distribution, with an average salary of $126,051 per year, or $60.6 per hour.

AI/ML(Python)-Mclean, VA-Only locals

StackNexus Inc.

Mclean, VA

Other

Posted 9 days ago

Job description

Note: Need only VA locals

Role:  AI/ML-Python

Location: McLean, VA (Onsite)

Interview: F2F Interview

Education & Experience

Minimum 7-10 years of overall software engineering experience with strong Python expertise

3+ years of hands-on experience building LLM-powered or AI/ML applications in production

Bachelor''''s/Master''''s degree in Computer Science, Engineering, AI/ML, or equivalent industry experience

Demonstrated experience owning end-to-end delivery of AI products from design to deployment

Python Fundamentals (Must Have)

Deep expertise in Python 3.10+, including asyncio, multithreading/multiprocessing, decorators, generators, and metaclasses

Proficiency with foundational packages: NumPy, Pandas, Pydantic, httpx/requests, dataclasses, typing

Strong grasp of clean code principles, SOLID design, and Pythonic idioms

Experience writing unit/integration tests with pytest and maintaining high code coverage

Familiarity with linting/formatting toolchains (ruff, black, isort, mypy) and pre-commit hooks

Experience with dependency and environment management (Poetry, uv, pip, venv, conda)

Agentic AI, LangChain & MCP (Core Focus)

Proven hands-on experience with Model Context Protocol (MCP) — designing, building, and maintaining MCP servers and clients

Strong working experience with FastMCP for building Python-based MCP servers with tools, resources, and prompts

Expert-level experience with LangChain (chains, agents, memory, retrievers, output parsers, LCEL)

Experience with LangGraph for stateful, multi-agent, and graph-based agentic workflows

Understanding of tool/function calling, structured outputs, and agent-to-agent communication patterns

Experience integrating multiple LLM providers (Anthropic Claude, OpenAI, Azure OpenAI, Gemini, open-source models)

Knowledge of RAG architecture: chunking strategies, embeddings, hybrid search, re-ranking, and evaluation

Backend & API Development

5+ years building production APIs with FastAPI, Flask, or Django REST Framework

Experience with streaming responses (SSE/WebSockets) for real-time LLM output

Solid understanding of authentication/authorization mechanisms (OAuth2, JWT, API key management)

Experience designing scalable microservices and event-driven architectures (Kafka, RabbitMQ, Celery)

Data & Storage

Strong SQL skills (PostgreSQL, MySQL) and experience with ORMs (SQLAlchemy)

Hands-on experience with vector databases: Chroma, Pinecone, Qdrant, Weaviate, pgvector, or FAISS

Experience with caching layers (Redis) and NoSQL stores (MongoDB, DynamoDB)

Data preprocessing, ETL pipeline development, and working with structured/unstructured data

ML/AI Foundations

Working knowledge of machine learning fundamentals: embeddings, similarity metrics, classification, evaluation

Familiarity with PyTorch, TensorFlow, or scikit-learn for model training/inference where needed

Experience with Hugging Face ecosystem (Transformers, datasets, model hub)

Understanding of prompt engineering, few-shot learning, and LLM evaluation frameworks (RAGAS, DeepEval, LangSmith evals)

Cloud, DevOps & MLOps

4+ years deploying applications on AWS, Azure, or Google Cloud Platform (Lambda, ECS/EKS, Cloud Run, Azure Functions)

Proficiency with Docker; working knowledge of Kubernetes and Helm

CI/CD experience with GitHub Actions, GitLab CI, or Azure DevOps

Experience with LLM observability and tracing tools (LangSmith, Langfuse, Arize Phoenix, OpenTelemetry)

Familiarity with secrets management, rate limiting, and cost monitoring for LLM workloads

Security & Responsible AI

Experience implementing guardrails, input/output validation, and PII handling in AI pipelines

Awareness of prompt injection risks and mitigation strategies in agentic/MCP-based systems

Understanding of compliance considerations (SOC 2, GDPR, HIPAA) when handling sensitive data

Collaboration & Leadership

Experience mentoring engineers, conducting code reviews, and setting technical standards

Ability to translate business problems into AI solution architectures

Excellent communication skills with both technical and non-technical stakeholders

Comfortable in Agile/Scrum delivery models with tools like Jira and Confluence

Nice to Have

Contributions to open-source AI/LLM projects (LangChain, MCP servers, etc.)

Experience with fine-tuning (LoRA/QLoRA) or self-hosted model serving (vLLM, Ollama, TGI)

Knowledge of A2A protocols, CrewAI, AutoGen, or other multi-agent frameworks

Experience building Slack/Teams bots or IDE integrations powered by MCP

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