Machine Learning Engineer
Chantilly, VA · On-site
... deep learning, and related fields. • Contribute to the development of best practices and ... Strong programming skills in Python and experience with relevant machine learning libraries and ...
Machine Learning Engineer
Chantilly, VA · On-site
... deep learning, and related fields. • Contribute to the development of best practices and ... Strong programming skills in Python and experience with relevant machine learning libraries and ...
Agentic AI Machine Learning Engineer
Arlington, VA · On-site
$95.10K - $126.80K/yr
... Deep Learning (DL), and Reinforcement Learning (RL), and with tools and AI agent frameworks such as LangChain, LangGraph, PydanticAI, or llamaindex • Experience in connecting Agents to APIs, Cloud ...
Agentic AI Machine Learning Engineer
Arlington, VA · On-site
$95.10K - $126.80K/yr
... Deep Learning (DL), and Reinforcement Learning (RL), and with tools and AI agent frameworks such as LangChain, LangGraph, PydanticAI, or llamaindex • Experience in connecting Agents to APIs, Cloud ...
Agentic AI Machine Learning Engineer
Annapolis Junction, MD · On-site
$84.30K - $112.40K/yr
... Deep Learning (DL), and Reinforcement Learning (RL), and with tools and AI agent frameworks such as LangChain, LangGraph, PydanticAI, or llamaindex • Experience in connecting Agents to APIs, Cloud ...
Agentic AI Machine Learning Engineer
Annapolis Junction, MD · On-site
$84.30K - $112.40K/yr
... Deep Learning (DL), and Reinforcement Learning (RL), and with tools and AI agent frameworks such as LangChain, LangGraph, PydanticAI, or llamaindex • Experience in connecting Agents to APIs, Cloud ...
Machine Learning Engineer
Herndon, VA · On-site
... deep learning, and related fields. • Contribute to the development of best practices and ... Strong programming skills in Python and experience with relevant machine learning libraries and ...
Machine Learning Engineer
Herndon, VA · On-site
... deep learning, and related fields. • Contribute to the development of best practices and ... Strong programming skills in Python and experience with relevant machine learning libraries and ...
SIMILAR CAREER TITLESData Scientist, AI Engineer, Deep Learning Engineer, Artificial Intelligence Engineer, Research Scientist, Data Engineer, NLP Engineer, Computer Vision Engineer, AI/ML Researcher ...
SIMILAR CAREER TITLESData Scientist, AI Engineer, Deep Learning Engineer, Artificial Intelligence Engineer, Research Scientist, Data Engineer, NLP Engineer, Computer Vision Engineer, AI/ML Researcher ...
SIMILAR CAREER TITLESData Scientist, AI Engineer, Deep Learning Engineer, Artificial Intelligence Engineer, Research Scientist, Data Engineer, NLP Engineer, Computer Vision Engineer, AI/ML Researcher ...
SIMILAR CAREER TITLESData Scientist, AI Engineer, Deep Learning Engineer, Artificial Intelligence Engineer, Research Scientist, Data Engineer, NLP Engineer, Computer Vision Engineer, AI/ML Researcher ...
SIMILAR CAREER TITLESData Scientist, AI Engineer, Deep Learning Engineer, Artificial Intelligence Engineer, Research Scientist, Data Engineer, NLP Engineer, Computer Vision Engineer, AI/ML Researcher ...
SIMILAR CAREER TITLESData Scientist, AI Engineer, Deep Learning Engineer, Artificial Intelligence Engineer, Research Scientist, Data Engineer, NLP Engineer, Computer Vision Engineer, AI/ML Researcher ...
Stay up-to-date with the latest advancements in machine learning, deep learning, and related fields ... Strong programming skills in Python and experience with relevant machine learning libraries and ...
Stay up-to-date with the latest advancements in machine learning, deep learning, and related fields ... Strong programming skills in Python and experience with relevant machine learning libraries and ...
SIMILAR CAREER TITLESData Scientist, AI Engineer, Deep Learning Engineer, Artificial Intelligence Engineer, Research Scientist, Data Engineer, NLP Engineer, Computer Vision Engineer, AI/ML Researcher ...
SIMILAR CAREER TITLESData Scientist, AI Engineer, Deep Learning Engineer, Artificial Intelligence Engineer, Research Scientist, Data Engineer, NLP Engineer, Computer Vision Engineer, AI/ML Researcher ...
... deep learning models at scale for computer vision (image recognition, object detection, image ... A blend of data engineering, machine learning, and product innovation skills that let you jump into ...
... deep learning models at scale for computer vision (image recognition, object detection, image ... A blend of data engineering, machine learning, and product innovation skills that let you jump into ...
Strong Python programming skills * Experience conducting machine learning/statistical experiments and manipulating data sets * Deep understanding and experience of machine learning, and deep learning ...
Strong Python programming skills * Experience conducting machine learning/statistical experiments and manipulating data sets * Deep understanding and experience of machine learning, and deep learning ...
Agentic AI Machine Learning Engineer
Annapolis, MD · On-site
$99K - $225K/yr
Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL ... Experience with programming, including ML frameworks such as TensorFlow, PyTorch, llama.cpp, and ...
Agentic AI Machine Learning Engineer
Annapolis, MD · On-site
$99K - $225K/yr
Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL ... Experience with programming, including ML frameworks such as TensorFlow, PyTorch, llama.cpp, and ...
Agentic AI Machine Learning Engineer
Washington, DC · On-site
$99K - $225K/yr
Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL ... Experience with programming, including ML frameworks such as TensorFlow, PyTorch, llama.cpp, and ...
Agentic AI Machine Learning Engineer
Washington, DC · On-site
$99K - $225K/yr
Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL ... Experience with programming, including ML frameworks such as TensorFlow, PyTorch, llama.cpp, and ...
Agentic AI Machine Learning Engineer
Washington, DC · On-site
$99K - $225K/yr
Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL ... Experience with programming, including ML frameworks such as TensorFlow, PyTorch, llama.cpp, and ...
New
Agentic AI Machine Learning Engineer
Washington, DC · On-site
$99K - $225K/yr
Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL ... Experience with programming, including ML frameworks such as TensorFlow, PyTorch, llama.cpp, and ...
New
Machine Learning Engineer
$102K - $144.38K/yr
Machine Learning Engineer II The Machine Learning Engineer II will be a member of the Learning and ... Proficiency with a deep learning framework, preferably PyTorch * Proficiency with basic libraries ...
Machine Learning Engineer
$102K - $144.38K/yr
Machine Learning Engineer II The Machine Learning Engineer II will be a member of the Learning and ... Proficiency with a deep learning framework, preferably PyTorch * Proficiency with basic libraries ...
Agentic AI Machine Learning Engineer
Arlington, VA · On-site
$99K - $225K/yr
Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL ... Experience with programming, including ML frameworks such as TensorFlow, PyTorch, llama.cpp, and ...
Agentic AI Machine Learning Engineer
Arlington, VA · On-site
$99K - $225K/yr
Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL ... Experience with programming, including ML frameworks such as TensorFlow, PyTorch, llama.cpp, and ...
Agentic AI Machine Learning Engineer
Alexandria, VA · On-site
$99K - $225K/yr
Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL ... Experience with programming, including ML frameworks such as TensorFlow, PyTorch, llama.cpp, and ...
Agentic AI Machine Learning Engineer
Alexandria, VA · On-site
$99K - $225K/yr
Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL ... Experience with programming, including ML frameworks such as TensorFlow, PyTorch, llama.cpp, and ...
Agentic AI Machine Learning Engineer
Washington, DC · On-site
$99K - $225K/yr
We're looking for an engineer like you to create artifi cia l intelligence ( AI ) and machine ... Experience with project work in deep learning, computer vision, NLP, or signal processing
Agentic AI Machine Learning Engineer
Washington, DC · On-site
$99K - $225K/yr
We're looking for an engineer like you to create artifi cia l intelligence ( AI ) and machine ... Experience with project work in deep learning, computer vision, NLP, or signal processing
Agentic AI Machine Learning Engineer
Annapolis Junction, MD · On-site
$99K - $225K/yr
Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL ... Experience with programming, including ML frameworks such as TensorFlow, PyTorch, llama.cpp, and ...
Agentic AI Machine Learning Engineer
Annapolis Junction, MD · On-site
$99K - $225K/yr
Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL ... Experience with programming, including ML frameworks such as TensorFlow, PyTorch, llama.cpp, and ...
Agentic AI Machine Learning Engineer
$99K - $225K/yr
Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL ... Experience with programming, including ML frameworks such as TensorFlow, PyTorch, llama.cpp, and ...
Agentic AI Machine Learning Engineer
$99K - $225K/yr
Experience with Large Language Models (LLM), Deep Learning (DL), and Reinforcement Learning (RL ... Experience with programming, including ML frameworks such as TensorFlow, PyTorch, llama.cpp, and ...
Deep Learning Developer information
What are the key skills and qualifications needed to thrive as a Deep Learning Developer, and why are they important?
To thrive as a Deep Learning Developer, you need a strong background in computer science, mathematics, and proficiency in programming languages like Python, often supported by a degree in a related field. Familiarity with deep learning frameworks such as TensorFlow or PyTorch, and experience with cloud platforms or GPU acceleration, are commonly required technical skills. Analytical thinking, problem-solving abilities, and effective teamwork distinguish top performers in this role. These competencies are crucial for designing, training, and deploying advanced neural network models that address complex real-world problems.
What are some common challenges Deep Learning Developers face when deploying models to production environments?
Deep Learning Developers often encounter challenges such as optimizing model performance for real-time inference, managing resource constraints (like GPU/CPU availability), and ensuring model reproducibility across different environments. Additionally, integrating deep learning models into existing software systems and maintaining them over time can be complex, especially as data and requirements evolve. Collaborating closely with DevOps, data engineers, and QA teams is essential to address these challenges and ensure smooth deployment and ongoing reliability.
What are Deep Learning Developers?
Deep Learning Developers are specialized software engineers or data scientists who design, build, and implement artificial intelligence systems using deep learning techniques. They work with neural networks, large datasets, and various frameworks like TensorFlow or PyTorch to develop models for tasks such as image recognition, natural language processing, and autonomous systems. Their responsibilities include data preprocessing, model training, optimization, and deployment to solve complex problems that require advanced pattern recognition. Deep Learning Developers often collaborate with AI researchers, data engineers, and product teams to integrate intelligent features into applications.
Which 3 jobs will survive AI?
Deep Learning Developers are likely to continue to be in demand as AI advances because they design and improve AI models, requiring specialized skills in programming, mathematics, and data analysis. Other resilient roles include AI ethicists, who address ethical considerations, and AI system trainers, who curate and annotate data to improve AI performance. These jobs involve complex problem-solving and human oversight that are less easily automated.
What is the difference between Deep Learning Developer vs Machine Learning Engineer?
| Aspect | Deep Learning Developer | Machine Learning Engineer |
|---|---|---|
| Required Credentials | Bachelor's or Master's in CS, AI, or related; experience with neural networks | Bachelor's or Master's in CS, Data Science, or related; knowledge of algorithms |
| Work Environment | Research labs, AI startups, tech companies focusing on neural networks | Data-driven companies, software firms, industries applying machine learning |
| Industry Usage | Primarily in AI research, neural network development, deep learning projects | Broader application including predictive modeling, data analysis, and ML systems |
Deep Learning Developers specialize in neural networks and deep learning models, often working on AI research and complex algorithms. Machine Learning Engineers have a broader focus on developing, deploying, and maintaining machine learning models across various applications. While both roles require similar educational backgrounds, their focus areas and industry applications differ.
What cities in Washington are hiring for Deep Learning Developer jobs? Cities in Washington with the most Deep Learning Developer job openings:
Full-time
Posted 19 days ago
Job description
Job Summary:
Dark Wolf constructs and deploys data management and analytics solutions for the defense and intelligence communities. They are seeking a highly motivated Machine Learning Engineer to design, develop, and implement machine learning models and algorithms to solve business problems.
Responsibilities:
• Design, develop, and implement machine learning models and algorithms to solve specific business problems.
• Build and maintain scalable and robust machine learning pipelines for data ingestion, preprocessing, feature engineering, model training, evaluation, and deployment.
• Transform machine learning models into deployable APIs and integrate them with existing applications and infrastructure.
• Collaborate closely with data scientists, software engineers, and product managers to understand requirements and translate them into practical ML solutions.
• Experiment with different machine learning techniques and algorithms to identify the most effective approaches for given problems.
• Evaluate model performance using appropriate metrics and iterate on models to improve accuracy, efficiency, and scalability.
• Monitor and maintain deployed models, ensuring their reliability and performance in production environments.
• Troubleshoot and resolve issues related to machine learning models and pipelines.
• Stay up-to-date with the latest advancements in machine learning, deep learning, and related fields.
• Contribute to the development of best practices and standards for machine learning development and deployment within the team.
• Document machine learning models, experiments, and deployment processes.
• Potentially work with large datasets and big data technologies.
• Optimize machine learning models for performance and efficiency.
Qualifications:
Required:
• Master’s in computer science, Machine Learning, or higher level degree is preferred with of 3+ years of related industry experience in Machine Learning, Computer Science, Data Science or related fields.
• Demonstrated hands-on experience in developing and deploying machine learning models in a production environment.
• Strong programming skills in Python and experience with relevant machine learning libraries and frameworks such as TensorFlow, Keras, PyTorch, scikit-learn, etc.
• Solid understanding of machine learning algorithms (e.g., regression, classification, clustering, dimensionality reduction, deep learning architectures).
• Experience with data preprocessing, feature engineering, and data visualization techniques.
• Familiarity with data storage and processing technologies (e.g., SQL, NoSQL databases, Spark, Hadoop).
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and their machine learning services.
• Understanding of software development principles, version control (e.g., Git), and CI/CD pipelines.
• Strong analytical and problem-solving skills with the ability to interpret data and draw meaningful conclusions.
• Excellent communication and collaboration skills to effectively communicate technical concepts to both technical and non-technical audiences.
Preferred:
• Experience with specific areas of machine learning such as Natural Language Processing (NLP), Computer Vision, or Recommender Systems.
• Experience with MLOps practices and tools for automating and monitoring machine learning workflows.
• Knowledge of containerization technologies like Docker and orchestration tools like Kubernetes.
• Experience with building and deploying RESTful APIs.
• Familiarity with big data technologies and distributed computing.
• Experience with statistical modeling and inference.
Company:
Dark Wolf provides DevSecOps agile software development, information operations, penetration testing and incident response, applied research and rapid prototyping, machine learning, and mission support and engineering services to the Intelligence Community, national security, and Fortune 500 customers. Founded in 2009, the company is headquartered in Herndon, USA, with a team of 501-1000 employees. The company is currently Late Stage.
Dark Wolf constructs and deploys data management and analytics solutions for the defense and intelligence communities. They are seeking a highly motivated Machine Learning Engineer to design, develop, and implement machine learning models and algorithms to solve business problems.
Responsibilities:
• Design, develop, and implement machine learning models and algorithms to solve specific business problems.
• Build and maintain scalable and robust machine learning pipelines for data ingestion, preprocessing, feature engineering, model training, evaluation, and deployment.
• Transform machine learning models into deployable APIs and integrate them with existing applications and infrastructure.
• Collaborate closely with data scientists, software engineers, and product managers to understand requirements and translate them into practical ML solutions.
• Experiment with different machine learning techniques and algorithms to identify the most effective approaches for given problems.
• Evaluate model performance using appropriate metrics and iterate on models to improve accuracy, efficiency, and scalability.
• Monitor and maintain deployed models, ensuring their reliability and performance in production environments.
• Troubleshoot and resolve issues related to machine learning models and pipelines.
• Stay up-to-date with the latest advancements in machine learning, deep learning, and related fields.
• Contribute to the development of best practices and standards for machine learning development and deployment within the team.
• Document machine learning models, experiments, and deployment processes.
• Potentially work with large datasets and big data technologies.
• Optimize machine learning models for performance and efficiency.
Qualifications:
Required:
• Master’s in computer science, Machine Learning, or higher level degree is preferred with of 3+ years of related industry experience in Machine Learning, Computer Science, Data Science or related fields.
• Demonstrated hands-on experience in developing and deploying machine learning models in a production environment.
• Strong programming skills in Python and experience with relevant machine learning libraries and frameworks such as TensorFlow, Keras, PyTorch, scikit-learn, etc.
• Solid understanding of machine learning algorithms (e.g., regression, classification, clustering, dimensionality reduction, deep learning architectures).
• Experience with data preprocessing, feature engineering, and data visualization techniques.
• Familiarity with data storage and processing technologies (e.g., SQL, NoSQL databases, Spark, Hadoop).
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and their machine learning services.
• Understanding of software development principles, version control (e.g., Git), and CI/CD pipelines.
• Strong analytical and problem-solving skills with the ability to interpret data and draw meaningful conclusions.
• Excellent communication and collaboration skills to effectively communicate technical concepts to both technical and non-technical audiences.
Preferred:
• Experience with specific areas of machine learning such as Natural Language Processing (NLP), Computer Vision, or Recommender Systems.
• Experience with MLOps practices and tools for automating and monitoring machine learning workflows.
• Knowledge of containerization technologies like Docker and orchestration tools like Kubernetes.
• Experience with building and deploying RESTful APIs.
• Familiarity with big data technologies and distributed computing.
• Experience with statistical modeling and inference.
Company:
Dark Wolf provides DevSecOps agile software development, information operations, penetration testing and incident response, applied research and rapid prototyping, machine learning, and mission support and engineering services to the Intelligence Community, national security, and Fortune 500 customers. Founded in 2009, the company is headquartered in Herndon, USA, with a team of 501-1000 employees. The company is currently Late Stage.