Job Description
We are seeking a highly skilled and experienced Machine Learning and Data Engineer to join our dynamic team. The ideal candidate will be responsible for designing, developing, and maintaining data pipelines and machine learning models, ensuring optimal performance and scalability. They will work closely with data scientists, software engineers, and business stakeholders to implement data-driven solutions and deploy machine learning models in production environments.
Responsibilities
- Design and develop scalable data pipelines and ETL processes to gather, process, and transform data from various sources.
- Build and deploy machine learning models using state-of-the-art algorithms and techniques.
- Maintain and optimize existing ML models to ensure performance and accuracy.
- Collaborate with data scientists and software engineers to integrate models into production systems.
- Conduct data preprocessing, feature engineering, and data wrangling for model training and evaluation.
- Develop and maintain data architectures, including databases and data warehouses.
- Implement data validation, data quality checks, and monitoring to ensure data integrity.
- Automate model training, testing, and deployment processes.
- Perform model evaluation and fine-tuning to enhance accuracy and efficiency.
- Develop and maintain comprehensive documentation for models and data pipelines.
- Stay updated with the latest trends and advancements in machine learning and data engineering.
Qualifications
- Bachelor’s or master’s degree in Computer Science, Data Science, Engineering, or related field.
- 5+ years of experience in data engineering and machine learning.
- Proficiency in programming languages like Python and Java.
- Strong hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Expertise in data processing tools like Apache Spark, Hadoop, and SQL.
- Familiarity with data visualization tools (e.g., Tableau, Power BI) and experience with libraries like Matplotlib.
- Proficiency in database technologies (SQL and NoSQL).
- Experience with cloud platforms (AWS, GCP, Azure) and containerization tools (Docker, Kubernetes).
- Strong problem-solving and analytical skills with a keen eye for detail.
- Excellent communication and collaboration abilities.
- Certification in Machine Learning, Data Science, or related fields.
- Experience with MLOps practices and tools (e.g., MLflow, Kubeflow).
- Knowledge of big data processing and real-time data streaming (Kafka, Apache Flink).
- Familiarity with data governance and data privacy standards.
Why Join Us?
Join a mission-driven team where your work directly will transform radiology through AI. mlHealth 360 is a global healthtech company transforming radiology with secure, cloud-native AI solutions. Our suite of medical imaging products improves diagnostic accuracy, reporting speed, and healthcare efficiency while seamlessly integrating into existing hospital systems. We offer a dynamic startup environment with opportunities for professional growth in the rapidly evolving field of digital health and AI regulation.
