Devitechs is hiring: Machine Learning Engineer Devi Technologies in Granite Heig
Devitechs, Granite Heights, WI, United States
✔️ Build large-scale machine learning solutions for classification, regression, clustering, and recommendation tasks.
✔️ Develop automated training pipelines, feature stores, and data transformations.
✔️ Implement ML systems capable of handling high-volume real-time data.
✔️ Create reusable libraries and frameworks for ML model development.
✔️ Perform model training, validation, and performance tuning using cloud GPU/TPU resources.
✔️ Collaborate with Data Scientists to transform prototypes into production systems.
✔️ Deploy ML models through REST APIs, streaming services, or serverless functions.
✔️ Implement monitoring tools to track model health, latency, and production failures.
✔️ Build robust data validation, testing, and quality control checks.
✔️ Maintain and optimize ML infrastructure for scalability and cost efficiency.
✔️ Use version control and experiment tracking tools like MLflow or Weights & Biases.
✔️ Incorporate responsible AI frameworks for fairness, transparency, and explainability.
✔️ Collaborate with business teams to integrate ML predictions into workflows.
✔️ Optimize models for edge devices, mobile platforms, or low-latency environments.
✔️ Troubleshoot production ML issues and perform root-cause analysis.
✔️ Benchmark model performance using industry-standard datasets and metrics.
✔️ Explore and implement deep learning, transformers, and generative AI solutions.
✔️ Document ML architectures, workflows, and project implementation details.
✔️ Participate in code reviews and mentoring of junior engineers.
✔️ Drive innovation by proposing new ML methodologies and tools.
#J-18808-Ljbffr
✔️ Develop automated training pipelines, feature stores, and data transformations.
✔️ Implement ML systems capable of handling high-volume real-time data.
✔️ Create reusable libraries and frameworks for ML model development.
✔️ Perform model training, validation, and performance tuning using cloud GPU/TPU resources.
✔️ Collaborate with Data Scientists to transform prototypes into production systems.
✔️ Deploy ML models through REST APIs, streaming services, or serverless functions.
✔️ Implement monitoring tools to track model health, latency, and production failures.
✔️ Build robust data validation, testing, and quality control checks.
✔️ Maintain and optimize ML infrastructure for scalability and cost efficiency.
✔️ Use version control and experiment tracking tools like MLflow or Weights & Biases.
✔️ Incorporate responsible AI frameworks for fairness, transparency, and explainability.
✔️ Collaborate with business teams to integrate ML predictions into workflows.
✔️ Optimize models for edge devices, mobile platforms, or low-latency environments.
✔️ Troubleshoot production ML issues and perform root-cause analysis.
✔️ Benchmark model performance using industry-standard datasets and metrics.
✔️ Explore and implement deep learning, transformers, and generative AI solutions.
✔️ Document ML architectures, workflows, and project implementation details.
✔️ Participate in code reviews and mentoring of junior engineers.
✔️ Drive innovation by proposing new ML methodologies and tools.
#J-18808-Ljbffr