The role involves preparing traffic data, developing and deploying machine learning models on Google Vertex AI, and collaborating with teams to improve project workflows.
This is a remote position.
Comerit is looking for an experienced and driven Google AI/ML Data Scientist to join our team and play a key role in the Border Wait Time (BWT) project. In this position, you will prepare and process complex traffic congestion datasets, develop machine learning models to predict traffic volumes, and deploy scalable solutions using Google Vertex AI. Your work will help improve real-time decision-making, enhance border efficiency, and optimize travel experiences for millions of users.
Requirements
Key Responsibilities
- Perform data cleaning, preprocessing, and feature engineering to prepare traffic congestion datasets for predictive modeling.
- Train, validate, and evaluate machine learning models to forecast traffic volumes based on historical trends and key features.
- Deploy machine learning models to Google Vertex AI to enable efficient and scalable prediction services.
- Monitor and validate model performance using test data, ensuring high accuracy and reliability.
- Refine models and methodologies based on performance metrics and stakeholder feedback.
- Collaborate with cross-functional teams, including cloud engineers, data engineers, and integration specialists, to integrate ML solutions into the BWT system.
- Stay updated with the latest advancements in AI/ML and incorporate best practices into project workflows.
Qualifications
Required:
- Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field.
- 3+ years of experience in machine learning, including data preprocessing, feature engineering, and model development.
- Proficiency in Python and ML libraries/frameworks such as TensorFlow, PyTorch, or scikit-learn.
- Hands-on experience with Google Cloud Platform (GCP), particularly Vertex AI, BigQuery, and Cloud Storage.
- Strong understanding of statistical modeling, time series analysis, and predictive analytics.
- Familiarity with version control tools (e.g., Git) and collaborative coding practices.
Preferred:
- Experience working with traffic or congestion datasets.
- Expertise in real-time data integration and analytics.
- Knowledge of containerization tools (e.g., Docker, Kubernetes) for deploying ML models.
- Understanding of data privacy and compliance considerations in cloud-based ML projects.
Similar Jobs
Fintech • Information Technology • Insurance • Financial Services • Big Data Analytics
Screen and process incoming Group Life claims and related mail, enter and update claims in the FEGLI system, handle claimant calls and correspondence, produce letters, perform peer reviews, and meet quality and production metrics.
Top Skills:
Fegli Claim SystemPc
Fintech • Information Technology • Insurance • Financial Services • Big Data Analytics
Reviews and approves escalated complaint responses, advises on complex life insurance and annuity transactions, investigates high-value disbursements and suspected fraud, and researches contract histories. The role develops resolutions for customers and partners, supports legal, compliance, product, and regulatory teams, identifies operational risks and trends, and recommends process improvements while maintaining strong controls.
Top Skills:
Microsoft CopilotMicrosoft Office Suite
Artificial Intelligence • Machine Learning • Natural Language Processing • Software • Conversational AI
Research Staff will develop foundational voice AI technologies, including low-bitrate neural audio codecs, steerable speech generation, disentangled audio representations, latent recombination, synthetic audio data generation, and multimodal speech-to-speech models. The role also involves designing scalable architectures, training methods, and inference algorithms optimized for hardware, billion-hour datasets, and real-time deployment. Candidates need strong mathematical foundations, foundation-model expertise, large-scale data pipeline experience, rigorous experimentation skills, deployment optimization knowledge, and publications or open-source contributions in speech or language AI.
Top Skills:
Data PipelinesFoundation ModelsGenerative ModelsGpu Hardware OptimizationLatent Space ModelsMultimodal LearningNeural Audio CodecsSelf-Supervised LearningSpeech-To-Speech SystemsStatistical Learning TheoryTriton Kernels
What you need to know about the Seattle Tech Scene
Home to tech titans like Microsoft and Amazon, Seattle punches far above its weight in innovation. But its surrounding mountains, sprinkled with world-famous hiking trails and climbing routes, make the city a destination for outdoorsy types as well. Established as a logging town before shifting to shipbuilding and logistics, the Emerald City is now known for its contributions to aerospace, software, biotech and cloud computing. And its status as a thriving tech ecosystem is attracting out-of-town companies looking to establish new tech and engineering hubs.
Key Facts About Seattle Tech
- Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Amazon, Microsoft, Meta, Google
- Key Industries: Artificial intelligence, cloud computing, software, biotechnology, game development
- Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Madrona, Fuse, Tola, Maveron
- Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute
