Senior Software Engineer - Machine Learning

Janea Systems (USA) is a dynamic team of the best & brightest software engineering specialists and solutions innovators, from around the world. From kernel to cloud, we provide high-impact software development services to Fortune 500 companies. 

We are seeking an exceptionally talented Senior ML Engineer to join our rapidly growing consulting team. In this role, 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. 

 

Location	Remote 100% / European residence required
Compensation	Salary
Work Schedule	Full time/ Flexible working hours
Reports to	Team Lead
Member of	Engineering Team

 

To be considered for this position, you must have the following qualifications: 

• 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, 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. 

Ideal candidates will also have: 

• Familiarity with big data technologies, such as Hadoop, Spark, or Hive is a plus.
• Any associate Cloud Certification is a plus. 

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.
   

Why join Janea? Because world-class talent deserves world-class opportunities. What we offer: 

• 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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