Position DescriptionWe are seeking an early-career AI Research Engineer to develop, optimize, and deploy machine learning models on resource-constrained (low size, weight, and power) platforms. This role focuses on bridging cutting-edge AI research with practical implementations that operate reliably under real-world constraints, including limited compute, noisy data, and degraded conditions.
The ideal candidate is motivated to make AI systems work outside of idealized settings-balancing performance, efficiency, and robustness.
Key Responsibilities- Investigate new algorithms, model architectures, and system approaches for efficient and robust AI
- Develop research concepts into working prototypes
- Develop and adapt machine learning models for deployment in low power and edge environments
- Prototype and evaluate AI systems using limited, noisy, or imperfect real-world data
- Collaborate with software and platform teams to integrate AI into end-to-end systems
- Evaluate system performance, robustness, repeatability and resource usage under real-world conditions
- Contribute to project leadership and participate in a culture of continuous learning, with opportunities to advance as a researcher and technical expert
Minimum Qualifications- Masters with 0-3 years of experience, or Bachelors with 3-5 years of experience, in Computer Science, Electrical Engineering, or a related field
- Experience developing, training, adapting and assessing machine learning models
- Strong programming skills in Python and experience with modern ML frameworks (e.g., PyTorch)
- Experience deploying ML models on edge or embedded systems
- Understanding of tradeoffs between accuracy, compute, latency, and energy
Preferred Qualifications- Hands-on experience with model optimization techniques such as quantization, pruning, and distillation
- Experience taking a model from training to deployed system is strongly preferred
- Familiarity with edge AI toolchains (e.g., TensorRT, ONNX Runtime, CUDA)
- Proficiency in C/C++ or other performance-oriented programming languages
- Experience developing software in a Linux environment
- Experience with CI/CD development pipelines
- Experience working with real-world sensor data, including limited or noisy datasets
- Experience evaluating system robustness under degraded conditions
- Familiarity with test & evaluation methodologies for ML systems
- Exposure to formal methods or verification approaches
Recent Graduate Hiring Range: $116,400 - $140,000
Experienced Hiring Range: $116,400 - $182,200
Disclaimer: MIT Lincoln Laboratory provides a typical hiring range as a good faith estimate of what we reasonably expect to offer for this position at the time of posting. The final salary offered to a selected candidate will depend on various factors, including-but not limited to-the scope and responsibilities of the role, the candidate's experience, skills and education/training, internal equity considerations and applicable legal requirements. This range reflects base salary only and does not include additional forms of compensation or benefits.At MIT Lincoln Laboratory, our exceptional career opportunities include many outstanding benefits to help you stay healthy, feel supported, and enjoy a fulfilling work-life balance. Benefits offered to employees include:
- Comprehensive health, dental, and vision plans
- MIT-funded pension
- Matching 401K
- Paid leave (including vacation, sick, parental, military, etc.)
- Tuition reimbursement and continuing education programs
- Mentorship programs
- A range of work-life balance options
- ... and much more!
Please visit our Benefits page for more information. As an employee of MIT, you can also take advantage of other voluntary benefits, discounts and perks.
Selected candidate will be subject to a pre-employment background investigation and must be able to obtain and maintain a Secret level DoD security clearance.
Requisition ID: 43335
