Senior Software Engineer - Machine Learning

June 15

🏡 Remote – Anywhere in California

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Logo of Janea Systems

Janea Systems

Solving enterprises' most complex software engineering challenges.

11 - 50

Description

• 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.

Requirements

• Bachelor's or Master’s degree in Computer Science or a related field. • 3+ years of experience as a Platform Engineer, ML DevOps 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, with the ability to break down complex challenges and develop innovative solutions. • Self-motivated and adaptable, with the ability to work effectively in fast-paced, dynamic environments.

Benefits

• Competitive compensation with benefits, paid vacation, and sick leave • The opportunity to work with a globally diverse team of top engineering talent on the industry’s toughest engineering challenges • 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. No business travel necessary. • 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.

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