Summary
Join Janea Systems (USA), a dynamic team of software engineering specialists and solutions innovators, as a Senior ML Engineer. You will have the opportunity to work on high-profile projects at the cutting edge of the software industry and help build our internal Machine Learning practice.
Requirements
- Bachelor's or Master’s degree in Computer Science or a related field
- 3+ years of experience as a Platform Engineer, ML Engineer, or Data Engineer
- Flexibility in experience with different programming languages and willingness to adjust to project needs
- Strong knowledge of machine learning algorithms, data pre-processing methods, and ML frameworks (such as PyTorch, TensorFlow, Keras)
- Experience with containers and Kubernetes in cloud environments (AWS, MS Azure, or GCP)
- Familiarity with data-oriented workflow orchestration frameworks (KubeFlow, Airflow, Argo)
- Experience with open source ML tools and ability to translate business needs into technical requirements
- Understanding of software testing, benchmarking, and continuous integration
- Excellent leadership, communication, and problem-solving skills
- Self-motivated and adaptable, with the ability to work effectively in fast-paced, dynamic environments
Responsibilities
- Drive the AI/ML practice at Janea Systems and develop strategies with clients
- Design scalable data pipelines and infrastructure for enterprise ML systems
- Implement offline models into production by developing real ML systems
- Collaborate with data scientists and software engineers to operationalize and deploy machine learning models in production environments
- Deploy scalable tools and services for machine learning training and inference
- Evaluate new technologies to improve ML system performance and reliability
- Apply software engineering best practices, including CI/CD, to ML development
- Facilitate the development and deployment of ML proof-of-concepts
- Review, refactor, optimize, containerize, deploy, version, and monitor data science models
- Implement monitoring and alerting solutions to ensure the reliability and performance of machine learning systems
- Optimize and automate the machine learning deployment process to ensure efficiency and reproducibility
- Collaborate with cross-functional teams to troubleshoot and resolve issues related to machine learning deployments
- Stay updated with industry trends and apply knowledge to drive innovation
- Promote industry best practices and enhance team expertise
Preferred Qualifications
- Familiarity with big data technologies, such as Hadoop, Spark, or Hive is a plus
- Any associate Cloud Certification is a plus
Benefits
- Competitive compensation with benefits
- Paid vacation and sick leave
- Ultra-flexible working conditions – we provide a generous office equipment allowance so you can work from home, we can also provide you with a desk at an office/coworking facility near you, or use both
- An enjoyable, start-up work environment, with excellent opportunities for professional growth and development
- Flexible working hours – as a remote-first company, our focus has always been on getting the job done well, not when or where it gets done
