Remote Senior Machine Learning Engineer - (Remote - Anywhere)

Description:

• Jobgether is seeking a Senior Machine Learning Engineer to join an innovative team focused on building and scaling automated, cloud-native solutions.
• The role involves designing and implementing advanced ML models and data workflows that drive real-world impact and cost optimization.
• The engineer will collaborate closely with data scientists, DevOps, and engineering teams to ensure seamless model deployment and system integration.
• Responsibilities include developing and maintaining robust machine learning pipelines for training, validation, and deployment.
• The engineer will collaborate cross-functionally to ensure production readiness of models and successful integration with existing systems.
• The role requires leveraging cloud-native tools to optimize ML workflows and infrastructure performance.
• The engineer will apply DevOps principles to streamline CI/CD processes and manage containerized environments.
• Ensuring compliance with data governance and security standards is also a key responsibility.
• The position encourages driving innovation by researching and applying the latest trends in ML, MLOps, and cloud technologies.

Requirements:

• Candidates must have proven experience in applied machine learning and data science, with a strong portfolio of deployed projects.
• Advanced proficiency in Python and experience with libraries such as pandas, scikit-learn, and PyTorch is required.
• A strong command of SQL and familiarity with large-scale data processing is necessary.
• Experience with cloud platforms such as AWS, GCP, or Azure is essential.
• A solid understanding of DevOps tools and practices, including Docker, Kubernetes, CI/CD, and infrastructure as code, is required.
• Hands-on experience building ML pipelines, from data ingestion to deployment and monitoring, is necessary.
• Excellent communication skills and the ability to thrive in a collaborative team environment are essential.

Benefits:

• Employees will work alongside highly skilled engineers and ML professionals.
• The company offers a flat organizational structure with direct access to leadership.
• There are short feedback loops and fast feature cycles, typically ranging from 1 to 4 weeks.
• The position provides flexible working hours and a remote-first environment.
• Equity options are available, allowing every team member to have a stake in the company.
• Employees are allocated 10% of their time for self-learning or personal projects.
• The work environment features minimal bureaucracy and maximum focus on impactful work.