Senior Machine Learning Engineer at TheIncLab

McLean, Virginia, United States -

Full Time

Start Date

Immediate

Expiry Date

23 Mar, 26

Salary

0.0

Posted On

23 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Neural Networks, Decision Trees, Ensemble Methods, Transformer-Based Models, Data Pipelines, Feature Engineering, Python, Optimization, Model Evaluation, Deep Learning, Data Validation, Software Engineering, Mentoring, Research, Collaboration

Industry

Software Development

Description

The Mission Starts Here TheIncLab engineers and delivers intelligent digital applications and platforms that revolutionize how our customers and mission-critical teams achieve success. We are where innovation meets purpose; and where your career can meet purpose as well. We are looking for a Senior Machine Learning Engineer to that will focus on researching, designing, training, and evaluating machine learning models to solve complex, real-world problems. We encourage you to apply and take the first step in joining our dynamic and impactful company. Your Mission, Should You Choose to Accept As a Machine Learning Engineer, you will research, evaluate, and select appropriate machine Learning approaches and architectures based on the problem definition. What will you do? Research, evaluate, and select appropriate machine learning approaches and architectures based on the problem definition Supervised, unsupervised, and reinforcement learning Neural networks, decision trees, ensemble methods Transformer-based models, adversarial networks, genetic algorithms Retrieval-Augmented Generation (RAG) where appropriate Design and implement machine learning models using frameworks such as PyTorch, TensorFlow, or equivalent Formulate and solve optimization problems using ML techniques Pathfinding and routing Combinatorial and constraint-based optimization Heuristic and learning-based optimization approaches Own data pipelines for ML systems Data validation and quality checks Feature engineering and preprocessing Data augmentation strategies for training robustness Train, tune, and debug models, addressing issues such as overfitting, instability, bias, and performance degradation Define and apply appropriate evaluation metrics, analyze results and iteratively improve model performance For transformer-based systems Optimize context window usage Manage token budgets, chunking strategies, and retrieval mechanisms Balance performance, accuracy, and computational cost Integrate ML models and data pipelines into production systems Make technical decisions and provide architectural guidance for ML systems Document experiments, results, and design decisions using tools such as Git, Jira, and Confluence Mentor junior engineers and guide best practices in ML development Stay current with emerging ML research, tools, and techniques Ability to travel up to 20% Capabilities that will enable your success Bachelor’s degree in Computer Science, Engineering, Applied Mathematics, or a related field 7+ years of professional experience, including significant hands-on machine learning development Strong understanding of machine learning theory and fundamentals Model selection and evaluation Bias/variance tradeoffs Optimization and loss functions Demonstrated experience training and evaluating models using frameworks such as PyTorch or TensorFlow Experience building and maintaining end-to-end ML pipelines Strong programming skills in Python (additional languages are a plus) Experience working with real-world, imperfect datasets Ability to explain model behavior, tradeoffs, and limitations to both technical and non-technical stakeholders Strong grasp of software engineering best practices and system design Preferred Qualifications Experience with deep learning architectures (CNNs, RNNs, Transformers) Experience applying ML to optimization, planning, or decision-making problems Familiarity with distributed training or large-scale data processing Experience with experiment tracking tools (e.g., MLflow, Weights & Biases) Experience deploying ML models into production (batch or real-time inference) Background in research-driven or R&D-focused engineering environments Clearance Requirements Applicants must be a U.S. Citizen and willing and eligible to obtain a U.S. Security Clearance at the Secret or Top-Secret level. Existing clearance is preferred. At TheIncLab we recognize that innovation thrives when employees are provided with ample support and resources. Our benefits packages reflect that: Hybrid and flexible work schedules Professional development programs Training and certification reimbursement e options for Me Extended and floating holiday schedule Paid time off and Paid volunteer time Health and Wellness Benefits includdical, Dental, and Vision insurance along with access to Wellness, Mental Health, and Employee Assistance Programs. 100% Company Paid Benefits that include STD, LTD, and Basic Life insurance. 401(k) Plan Options with employer matching Incentive bonuses for eligible clearances, performance, and employee referrals. A company culture that values your individual strengths, career goals, and contributions to the team About TheIncLab Founded in 2015, TheIncLab (“TIL”) is the first human-centered artificial intelligence (AI+X) lab. We engineer complex, integrated solutions that combine cutting-edge AI technologies with emerging systems-of-systems to solve some of the most difficult challenges in the defense and aerospace industries. Our work spans diverse technological landscapes, from rapid ideation and prototyping to deployment. At TIL, we foster a culture of relentless optimism. No problem is too hard, no project is too big, and no challenge is too complex to tackle. This is possible due to the positive attitude of our teams. We approach every problem with a “yes” attitude and focus on results. Our motto, “demo or die,” encompasses the idea that failure is not an option. We do all of this with a work ethic rooted in kindness and professionalism. The positive attitude of our teams is only possible due to the support TIL provides to each individual. At TIL, we believe that every challenge is an opportunity for growth and innovation. Our teams are encouraged to think outside the box and come up with creative solutions to complex problems. We understand that the path to success is not always straightforward, but we are committed to persevering and finding a way forward. Our culture of relentless optimism is not just about having a positive attitude; it is about taking action and making things happen. We believe in the power of collaboration and teamwork, and we know that by working together, we can achieve great things. Our teams are made up of individuals who are passionate about their work and dedicated to making a difference. Learn more about TheIncLab and our job opportunities at www.theinclab.com. *Salary range guidance provided is not a guarantee of compensation. Offers of employment may be at a salary range that is outside of this range and will be based on qualifications, experience, and possible contractual requirements. *This is a direct hire position, and we do not accept resumes from third-party recruiters or agencies.

Responsibilities

As a Senior Machine Learning Engineer, you will research, evaluate, and select appropriate machine learning approaches and architectures based on problem definitions. You will also design and implement machine learning models and integrate them into production systems.