**Please note - Actively hiring for this position in the San Diego, CA area** As a Machine Learning Engineer, you will play a critical role in developing cutting-edge models and algorithms that transform data into actionable insights. You will collaborate with cross-functional teams, work on challenging projects, and work building one of our new exciting products in the environmental devices industry. This role is a contractor role, with strong opportunities for permanent hiring and growth. If you have a strong foundation in machine learning frameworks, data manipulation, and model optimization, and are eager to apply your skills in a fast-paced, innovative environment, we would love to hear from you. Our values: + Prudent optimism …glass-half-full, with a dose of caution to challenge our assumptions. + Intrinsic motivation …driven by autonomy, goal clarity, and regular feedback. + Commit to desired outcomes …define desired outcomes and achieve them vigorously. + No egos, no jerks …no joke. You will be responsible for: + Expertise in ML frameworks and common ML libraries (TensorFlow, Keras, PyTorch, etc.). + Expertise in data manipulation and analysis skills. Should be comfortable with affiliated libraries (Pandas, NumPy, SciPy, etc.). + Understanding of a wide range of ML algorithms (SVMs, neural networks, clustering algorithms, etc.) and ensemble methods. + Experience with selecting appropriate models for various tasks, and understanding of how to improve models given their performance evaluations. + Expertise in feature selection, feature extraction, and feature engineering. + Deep learning expertise (knowledge of designing and implementing multiple neural network architectures, experience with transfer learning techniques, proficiency in tuning hyperparameters). + Data science skills (data analytics and visualization). Qualifications: + 2 to 5 years relevant industry experience with Machine Learning, Statistics, Data Engineering, or similar + Experience with device development, robotics preferred + Strong understanding of data structures or algorithms + Familiar with hybrid models that integrate multiple data sources + Experienced with FCNNs (fully connected neural networks) and pre-trained CNNs + Comfortable with feature engineering, especially for unconventional classification models + Experienced with a wide range of modeling approaches such as SVMs and clustering algorithms Preferred skills: + Experience taking ideas from inception to launch + Understanding of product market fit, user experience, analytics, metrics and testing + Experience working with highly scalable, fault-tolerant, secure and compliant architecture and systems + Strong communication skills and bias for action + Familiar with holographic data processing