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.
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.).
Design multi‑class object detection and classification pipelines for noisy, imbalanced datasets.
Define evaluation metrics including confusion matrices, calibration, and class‑wise scoring.
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.
Work with hardware, software, product and cross-functional teams.
Communicate technical decisions and trade‑offs to senior stakeholders.

Requirements

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.

Benefits

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

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

XGBoostRandom ForestsSVMCNNTransformershyperparameter tuningfeature selectionalgorithm evaluationPythonC++

Soft Skills

communicationleadershipcollaborationproblem-solvinganalytical thinking