Machine Learning Engineer

Job Title: Machine Learning Engineer

Location: Fort Meade, MD

Required Clearance : TS/SCI w/ Full-Scope Poly

Salary: Competitive


We are seeking a highly skilled and motivated Machine Learning Engineer to join our dynamic team. The ideal candidate will have a strong background in machine learning, data science, and software engineering. You will work closely with data scientists, engineers, and product managers to design, develop, and deploy machine learning models and solutions that drive business value.



Key Responsibilities:

• Design, develop, and implement machine learning models and algorithms to solve real-world problems.
• Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
• Conduct data analysis and preprocessing to ensure high-quality data for model training.
• Optimize and fine-tune models for performance, accuracy, and scalability.
• Deploy machine learning models into production and monitor their performance.
• Develop and maintain machine learning pipelines and infrastructure.
• Stay current with the latest research and advancements in machine learning and AI.
• Participate in code reviews, team meetings, and contribute to a collaborative development environment.
• Document processes, models, and findings comprehensively.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field. Ph.D. is a plus.
• Proven experience as a Machine Learning Engineer or in a similar role.
• Strong proficiency in programming languages such as Python, R, or Java.
• Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, etc.
• Solid understanding of machine learning algorithms, including supervised and unsupervised learning, reinforcement learning, and deep learning.
• Experience with data processing tools like Pandas, NumPy, and data visualization tools such as Matplotlib or Seaborn.
• Familiarity with cloud platforms like AWS, Google Cloud, or Azure for model deployment and scaling.
• Strong problem-solving skills and the ability to think critically and analytically.
• Excellent communication and teamwork skills.

Preferred Qualifications:

• Experience with natural language processing (NLP) and computer vision.
• Familiarity with big data technologies such as Hadoop, Spark, or Kafka.
• Knowledge of software development best practices and version control systems like Git.
• Experience with containerization tools like Docker and orchestration tools like Kubernetes.
• Previous experience in a fast-paced, startup environment.