Senior AI/Machine Learning Engineer

🌍 Remote, USA 🎯 Full-time 🕐 Posted Recently

Job Description

The Elevator Pitch

Join Evolv as Senior AI/Machine Learning Engineer to advance AI innovation in physical security technology. As a key team member of the AI/ML team, you will be developing and deploying state-of-the-art machine learning and deep learning solutions. Your role will involve leveraging diverse data sources, including magnetic sensors, 3D cameras and other sensors, to create multi-sensor fusion solutions that operate in real-time on constrained hardware platforms. This hands-on role requires deep expertise in classical ML, deep learning, feature engineering, model optimization, and MLOps. You will drive modeling strategy, strengthen model accuracy and robustness, and deploy reliable models in real-world environments. This position is ideal for someone known for measurably improving models—not just building them.

Success in the Role: What performance outcomes will you work toward in the first 6–12 months?

Learn the sensor ecosystem, ML pipelines, and development standards.
Review real-time constraints, production workflows, and existing model performance baselines.
Engage in code reviews and collaborate across engineering teams.
Identify key opportunities for improving accuracy, latency, and robustness.

Lead feature engineering from raw sensor inputs, including temporal, spectral, and statistical features.
Develop and optimize classical ML and deep learning models.
Propose model improvements through systematic experimentation and benchmarking.
Partner with product and hardware teams to translate sensor behavior into ML architectures.

Own end‑to‑end ML model lifecycle for core production systems.
Deploy scalable ML models and ensure operational reliability.
Drive architecture decisions balancing classical ML and deep learning approaches.
Improve robustness across devices and field environments by modeling sensor characteristics.

The Work: What type of work will you be doing? What assignments, requirements, or skills will you be performing on a regular basis?

Design, develop, and optimize ML models—including XGBoost, Random Forests, SVMs, CNNs, and Transformers.
Lead hyperparameter tuning, feature selection, and algorithm evaluation.
Integrate models to production system, work with SW team on optimizing runtime speed and performance
Develop reproducible training pipelines with model, data, and experiment versioning.
Feature Engineering & Sensor‑Aware Modeling.
Extract temporal, spectral, and domain‑specific features from raw sensor signals.
Use data analytics tools such as UMAP and T-SNE to understand data distribution and feature characteristics.
Model sensor characteristics such as noise, bias, drift, and environmental effects.
Perform ablation studies and feature importance analyses (SHAP, PDP, etc.).
Multi‑Class Detection & Classification:
Design multi‑class object detection and classification pipelines for noisy, imbalanced datasets.
Define evaluation metrics including confusion matrices, calibration, and class‑wise scoring.
MLOps & Production Excellence:
Deploy production‑ready ML code impacting real customers.
Ensure reliability through CI/CD, drift detection, and data validation.
Optimize models for edge and compute‑constrained environments.
Cross‑Functional Collaboration:
Work with hardware, software, product and cross-functional teams.
Communicate technical decisions and trade‑offs to senior stakeholders.

Qualifications

Master’s or PhD in Computer Science, Machine Learning, Engineering, Applied Math, Physics, or related field.
3- 5+ years building and deploying ML models for real-world applications
Strong expertise in classical ML techniques (e.g., XGBoost, Random Forests, SVM, k‑NN) and modern ML techniques (e.g., deep neural network, transformers).
Proficiency in Python, ML libraries (scikit‑learn, NumPy, pandas) and C++
Experience with multi‑class classification on real‑world, noisy datasets.
Strong statistical and model evaluation skills.

Experience with sensor or time‑series data (magnetic, radar, 3D, IoT).
Advanced feature extraction (FFT, windowing, frequency domain).
Experience with imbalanced datasets and label quality challenges.
Familiarity with feature importance and interpretability tools
MLOps experience: MLflow/W&B, CI/CD for ML, drift detection.
Experience optimizing models for edge devices.

Redesign a multi‑class sensor‑based classification pipeline for improved accuracy, stability, and inference speed.
Develop ML architectures that explicitly model sensor behavior and failure modes.
Build a comparative framework for evaluating classical ML vs. deep learning models.
Own the end‑to‑end lifecycle of a core production ML system.

What is leadership like for this role? What is the structure and culture of the team?

You will join our R&D organization, reporting directly to VP of ML and sensors. In this role, you will interface with cross-disciplinary teams of highly skilled and autonomous engineers with expertise in Electromagnetics, Computer Vision, and AI. Our R&D organization includes more than 100 dedicated developers, engineers, scientists, managers and directors, each bringing deep technical knowledge and a strong culture of collaboration and support.

The team culture is one based on building trust, collaboration, on-going development through kindness, authenticity, courage, drive, and fun!

Where is the role located? This role is based at our headquarters in Waltham, Massachusetts. Due to the nature of our software-enabled hardware products, this position requires a minimum of 60% or 3 days on-site work.

What is the salary range? The base salary range for this full-time position is $152,000 to $198,000. Our salary ranges are determined by role, level, and location.

The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

· Please note that the compensation details listed in role posting reflect the base salary only, and do not include commission, equity, or benefits

Do the right thing, always;
Put people first'
Own it;
Win together; and continue to
Be bold, stay curious.

Equity as part of your total compensation package
Medical, dental, and vision insurance
Health Savings Account (HSA)
A 401(k) plan (and 2% company match)
Flexible Paid Time Off (PTO)- take the time you need to recharge, with manager approval and business needs in mind
Quarterly stipend for perks and benefits that matter most to you
Tuition reimbursement to support your ongoing learning and development
Subscription to Calm

Evolv Technology (“Evolv”) is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind. We welcome and encourage diversity in the workplace, and all employment decisions are made without regard to race, color, religion, national, social or ethnic origin, sex (including pregnancy), age, disability, HIV Status, sexual orientation, gender identity and/or expression, veteran status, or any other status protected by law in the locations where we operate. Evolv will not tolerate discrimination or harassment based on any of these characteristics.

Evolv is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. If you need a reasonable accommodation as part of the job application process, please connect with us at [email protected].

Evolv participates in E-verify for all employees after the completion of Form I-9.

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