Role overview
We’re seeking a passionate and skilled Machine Learning Engineer to join our growing team in the Erskine or Newcastle area. You’ll play a key role in designing, developing, and deploying scalable ML solutions across a variety of domains. This is a fantastic opportunity to work with cutting-edge technologies and contribute to impactful projects in a collaborative, innovation-driven environment.
What you'll work on
- Design and implement robust machine learning models using modern frameworks and libraries.
- Collaborate with data scientists, engineers, and stakeholders to translate business requirements into technical solutions.
- Optimize and deploy models using tools like TensorFlow Serving, TorchServe, ONNX, and TensorRT.
- Build and manage ML pipelines using MLflow, Kubeflow, and Azure ML Pipelines.
- Work with large-scale data using PySpark and integrate models into production environments.
- Monitor model performance and retrain as needed to ensure accuracy and efficiency.
- Collaborate with cross-functional teams to integrate AI solutions into scalable products
- Ensure best practices in data engineering and contribute to architectural decisions
- Contribute to the mentoring and development of junior team members.
- Support senior team members in identifying and addressing data science opportunities.
What we're looking for
- Strong proficiency in Python and ML libraries such as:
- pandas, NumPy, scikit-learn
- XGBoost, LightGBM, CatBoost
- TensorFlow, Keras, PyTorch
- Experience with model deployment and serving tools:
- ONNX, TensorRT, TensorFlow Serving, TorchServe
- Familiarity with ML lifecycle tools:
- MLflow, Kubeflow, Azure ML Pipelines
- Experience working with distributed data processing using PySpark.
- Solid understanding of software engineering principles and version control (e.g., Git).
- Excellent problem-solving skills and ability to work independently or in a team.
- Strong proficiency in Python and ML libraries such as:
- pandas, NumPy, scikit-learn
- XGBoost, LightGBM, CatBoost
- TensorFlow, Keras, PyTorch
- Experience with model deployment and serving tools:
- ONNX, TensorRT, TensorFlow Serving, TorchServe
- Familiarity with ML lifecycle tools:
- MLflow, Kubeflow, Azure ML Pipelines
- Experience working with distributed data processing using PySpark.
- Solid understanding of software engineering principles and version control (e.g., Git).
- Excellent problem-solving skills and ability to work independently or in a team.
- Typically, 6+ years of relevant work experience in industry, with a minimum of 2+ years in a similar role.
- Proficiencies in data cleansing, exploratory data analysis, and data visualization
- Continuous learner that stays abreast with industry knowledge and technology
Tags & focus areas
Used for matching and alerts on DevFound Fulltime Remote Machine Learning Data Science Tensorflow Ai