Data Scientist

As a Data Scientist, you will be responsible for building, training, and optimizing ML model architectures to enhance performance and scalability. You will develop and deploy machine learning models aligned with product objectives, research and refine sensor processing algorithms, and improve data collection and annotation pipelines. The role involves innovating methods for real-world data acquisition, evaluating models, and collaborating with cross-functional teams to integrate models and data processing.

Must Have

• Hands-on experience with computer vision and deep learning projects.
• Strong understanding of deep learning algorithms and architectures (CNNs, object detection, segmentation, etc.).
• Proficiency in Python and experience with C/C++ for performance-critical tasks.
• Expertise with ML frameworks: PyTorch, TensorFlow, Keras.
• Proficiency with data libraries: NumPy, Pandas.
• Experience training models with real-world data, including data collection and annotation.
• Experience optimizing models for edge computing (quantization, pruning, ONNX, TensorRT).
• Familiarity with MLOps tools or workflow automation (e.g., MLflow, Weights & Biases, Airflow).
• Ability to analyze datasets, interpret model performance, and debug ML workflows.
• Experience with automated training and testing pipelines.
• Strong analytical and problem-solving skills with the ability to explain findings clearly.
• Excellent written and verbal communication skills.

Good to Have

• Knowledge of sensor fusion, time-series data, or other advanced signal processing techniques.
• Experience with SageMaker, Bedrock
• Experience deploying models into production-grade systems or embedded devices.
• Exposure to cloud platforms (AWS/GCP/Azure) for ML training or deployment.
• Experience working in a startup environment, adapting to fast-paced and evolving requirements.

Perks & Benefits

• Contribute directly to the core AI technology at a high-growth startup.
• Work on cutting-edge ML challenges with real-world impact.
• Collaborate with a skilled, multidisciplinary team of engineers and scientists.
• Enjoy a culture that values creativity, experimentation, and technical excellence.
• Competitive compensation with opportunities for rapid growth and ownership.

Key Responsibilities

• Build, train, and optimize ML model architectures to improve performance and scalability.
• Develop and deploy machine learning models aligned with program and product objectives.
• Research, evaluate, and refine sensor processing algorithms under the direction of the Lead Data Scientist.
• Enhance sensor data collection, transformation, and annotation pipelines.
• Innovate methods for real-world data acquisition and labeling.
• Train, test, and evaluate models; document findings and propose improvements.
• Work with cross-functional teams to define, develop, and integrate models and data processing pipelines.

Must-Have Skills & Experience

• Hands-on experience with computer vision and deep learning projects.
• Strong understanding of deep learning algorithms and architectures (CNNs, object detection, segmentation, etc.).
• Proficiency in Python and experience with C/C++ for performance-critical tasks.
• Expertise with ML frameworks: PyTorch, TensorFlow, Keras.
• Proficiency with data libraries: NumPy, Pandas.
• Experience training models with real-world data, including data collection and annotation.
• Experience optimizing models for edge computing (quantization, pruning, ONNX, TensorRT).
• Familiarity with MLOps tools or workflow automation (e.g., MLflow, Weights & Biases, Airflow).
• Ability to analyze datasets, interpret model performance, and debug ML workflows.
• Experience with automated training and testing pipelines.
• Strong analytical and problem-solving skills with the ability to explain findings clearly.
• Excellent written and verbal communication skills.

Nice-to-Have Skills

• Knowledge of sensor fusion, time-series data, or other advanced signal processing techniques.
• Experience with SageMaker, Bedrock
• Experience deploying models into production-grade systems or embedded devices.
• Exposure to cloud platforms (AWS/GCP/Azure) for ML training or deployment.
• Experience working in a startup environment, adapting to fast-paced and evolving requirements.

Qualifications

• MS or PhD in Machine Learning, Data Science, Computer Science, Engineering, Applied Math, or a related field.
• Passion for working with real-world data and deploying models into production environments.
• This position requires working directly or indirectly with the US Government in restricted environments. Candidates must be U.S. citizens or lawful permanent residents (Green Card holder).

Why Join Us

• Contribute directly to the core AI technology at a high-growth startup.
• Work on cutting-edge ML challenges with real-world impact.
• Collaborate with a skilled, multidisciplinary team of engineers and scientists.
• Enjoy a culture that values creativity, experimentation, and technical excellence.
• Competitive compensation with opportunities for rapid growth and ownership.