Senior AI Engineer
honeycomb.io
GoPythonRubyTypeScript
AI/ML Engineer
Fortive
full-time
Posted on:
Location Type: Remote
Location: Remote • 🇺🇸 United States
Visit company websiteJob Level
Mid-LevelSenior
Tech Stack
AirflowAzureCloudDockerKubernetesMicroservices.NETPythonPyTorchScikit-LearnTensorflow
About the role
- Design, develop, and deploy scalable machine learning models and AI solutions for Provation’s products.
- Implement best practices in AI/ML model development, including data preprocessing, feature engineering, model training, and optimization.
- Work closely with Product Management, Data Science, and Engineering to evaluate, develop, and maintain innovative AI-powered solutions.
- Manage and scale data pipelines to support AI/ML workflows, ensuring efficient data availability for training and inference.
- Research and implement state-of-the-art AI/ML techniques, including deep learning, NLP, computer vision, and generative AI.
- Develop and manage MLOps workflows, ensuring model monitoring, retraining, and governance in production.
- Collaborate with DevOps and software engineering teams to deploy AI models in cloud environments including integration of AI/ML models with .NET microservices and Kubernetes.
- Ensure compliance with security, ethical AI, and regulatory requirements (e.g., HIPAA, GDPR) when working with sensitive data.
- Develop and implement methods to measure the accuracy and effectiveness of AI solutions, ensuring continuous improvement and adherence to performance standards.
- Participate in Agile development processes, including daily stand-ups, sprint planning, and code reviews.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field, or equivalent experience.
- Proven experience as an AI/ML Engineer, Data Scientist, or related role with a strong focus on developing AI/ML-driven solutions.
- Strong proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Experience with generative AI and large language models (LLMs), including their development, deployment, and optimization.
- Hands-on experience in building and optimizing deep learning models for NLP, computer vision, or time-series forecasting.
- Experience working with cloud-based AI/ML platforms (Azure ML, Azure AI Foundry).
- Solid understanding of data structures, algorithms, and distributed computing.
- Knowledge of MLOps principles and experience with tools such as MLflow, Kubeflow, or Airflow.
- Experience with C# and .NET.
- Experience deploying AI/ML models in containerized environments (Docker, Kubernetes) is a plus.
- Strong understanding of AI ethics, data privacy, and security considerations.
Benefits
- Competitive base pay
- Health insurance
- Flexible spending accounts
- Health savings accounts
- Retirement savings plans
- Life and disability insurance programs
- Paid and unpaid time away from work
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
machine learningAI solutionsdata preprocessingfeature engineeringmodel trainingmodel optimizationdeep learningnatural language processingcomputer visiongenerative AI
Soft skills
collaborationcommunicationproblem-solvingagile developmentteamworkinnovationadaptabilitycritical thinkingtime managementattention to detail
