Sr Machine Learning Engineer Santa Clara, CA

Blue River Technology; Santa Clara, Northern (CA, KY); Hybrid; USD 149,000 - 275,000; Full time

Benefits offered by this job

Bonus eligibility

Job summary

Blue River Technology is seeking a Sr Machine Learning Engineer in Santa Clara, CA. You will implement deep-learning models for scene segmentation and depth estimation to support autonomous agricultural and construction robotics.

You will use multi-sensor data (vision, radar, thermal) and optimize for accuracy, latency, and robustness. You will design end-to-end ML pipelines, evaluate inference performance on diverse HPC/GPU hardware, and collaborate across engineering teams to deploy real-time

Qualifications

• Bachelor's degree in Computer Science, Electrical Engineering, Computer Engineering, or related field plus 1 year and 6 months of related experience.
• Train and optimize computer vision models for object detection, semantic segmentation, and depth estimation using supervised and self-supervised learning.
• Build and evaluate deep learning models using PyTorch and TensorFlow, with transfer learning and distributed training.
• Evaluate model inference performance across HPC GPUs and NVIDIA devices for real-time execution.
• Design end-to-end ML pipelines for data ingestion, training, validation, and deployment.
• Integrate synthetic data and domain alignment for CV model training.
• Research transformer-based backbones and advanced loss functions to improve accuracy.
• Perform dataset curation and active learning to improve data quality and reduce false positives.

Responsibilities

• Implement deep-learning models and frameworks for scene segmentation, depth estimation, active learning, and situational awareness for autonomous vehicles in construction/agriculture.
• Build and evaluate ML models using data from vision, radar, and thermal cameras, assessing accuracy, robustness, and latency.
• Research new methods to improve detection performance and processing speed.
• Collaborate with robotics engineers to deploy algorithms on real-time field platforms.
• Work with systems engineers to maintain data-processing and annotation pipelines for monitoring and improvement.

Skills

CV model training

PyTorch

TensorFlow

Model evaluation

Active learning

End-to-end ML pipelines

Domain adaptation

Transformer backbones

Hyperparameter tuning

Education

Bachelor's degree in CS/EE/CE

Job description

Title and Location: Sr Machine Learning Engineer in Santa Clara, CA.

Job Responsibilities

• Implement deep-learning models and frameworks for scene segmentation, depth estimation, active learning, and the development of situational awareness for autonomous vehicles operating in construction and agriculture environments.
• Build and evaluate machine-learning models using data from multiple sensor modalities, including vision, radar, and thermal cameras, and assess trade-offs in accuracy, robustness, and latency.
• Research and develop new methods to improve detection performance and increase processing speed.
• Collaborate with robotics engineers to transition algorithms from desktop and server-class systems to real-time field-deployed robotic platforms.
• Work with systems and software engineers to design and maintain data-processing and annotation pipelines that support continuous system monitoring, evaluation, and improvement.

Qualifications

• Bachelor’s degree in Computer Science, Electrical Engineering, Computer Engineering, or related field plus 1 year and 6 months of related experience.
• Required skills:
  • Train and optimize computer vision models for object detection, semantic segmentation, and monocular/stereo depth estimation using supervised and self-supervised learning, including loss function customization and multi-scale model training (1 yr, 6 mos).
  • Build and evaluate deep learning models using PyTorch and TensorFlow, implementing transfer learning, custom training loops, distributed training, gradient-based optimization, and hyperparameter tuning for large-scale image datasets (1 yr, 6 mos).
  • Evaluate model inference performance and runtime behavior across heterogeneous hardware platforms, including high-performance computing (HPC) GPU environments, local NVIDIA GPU development systems, and VPU-based inference on production deployment machines, to ensure real-time execution requirements are met (1 yr, 6 mos).
  • Design and implement end-to-end ML pipelines for data ingestion, preprocessing, model training, validation, experiment tracking, and deployment using reproducible workflows and version-controlled environments (1 yr, 6 mos).
  • Integrate and validate synthetic image datasets for computer vision model training, including domain alignment, data normalization, camera parameter adjustment, and evaluation of generalization performance against real-world datasets (1 yr, 6 mos).
  • Research and implement emerging computer vision architectures and training strategies, including transformer-based backbones, advanced loss functions, and optimization techniques, to improve model accuracy and inference efficiency (1 yr, 6 mos).
  • Perform dataset curation, large-scale image preprocessing, exploratory error analysis, and implement active learning strategies based on model uncertainty and diversity sampling to improve training data quality and reduce false positives (1 yr, 6 mos).
• 5% domestic travel required to visit testing facilities and customer sites. May work remotely; periodic time in office required; must live within commuting distance of office.

The US annual base salary range for this position is $149,365 - $275,000, along with eligibility for Blue River’s bonus and benefit programs.