Remote Machine Learning Engineer

Description:

• As a Pythian Machine Learning Engineer, you will focus on building and optimizing machine learning pipelines, deploying models to production, and ensuring their scalability and reliability.
• You will be responsible for integrating machine learning models into various products and client solutions, with an emphasis on utilizing pre-trained models like Large Language Models (LLMs) and other AI-driven technologies.
• Your role will involve collaboration with cross-functional teams to develop and maintain robust, efficient, and scalable machine learning systems.
• You will design, develop, and maintain machine learning pipelines for internal and client-driven projects.
• You will deploy machine learning models, including pre-trained models (e.g., LLMs), into production environments and ensure scalability and performance.
• You will collaborate with data scientists to translate models into production-ready systems that meet business requirements.
• You will optimize and tune machine learning models for performance, reliability, and cost-efficiency.
• You will integrate machine learning models with cloud platforms and other infrastructure (e.g., AWS, GCP, Azure).
• You will implement model monitoring, logging, and maintenance systems to ensure continuous operation and improvement of deployed models.
• You will work closely with software engineering teams to ensure seamless model integration into larger applications.
• You will stay up to date with the latest advancements in machine learning engineering, infrastructure, and deployment technologies.

Requirements:

• A Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field is required; a Ph.D. is a plus.
• You must have 3+ years of experience in machine learning engineering, software engineering, or a related role.
• Strong programming skills in Python, Java, or similar languages are required, with proficiency in ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Hands-on experience with deploying pre-trained models, such as Large Language Models (LLMs), into production environments is necessary.
• Experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes) is required.
• A solid understanding of data pipelines, ETL processes, and version control systems (e.g., Git) is essential.
• You should have experience in building scalable, distributed systems and optimizing machine learning models for performance.
• Familiarity with MLOps tools and practices, including model versioning, monitoring, and CI/CD pipelines, is important.
• Strong communication skills and the ability to collaborate with cross-functional teams, including data scientists and engineers, are required.

Benefits:

• You will receive a competitive total rewards package with excellent take-home salaries, a shifted work time bonus (if applicable), and an annual bonus plan.
• An annual training allowance is provided to hone your skills or learn new ones; you will also receive 2 paid professional development days, and opportunities to attend conferences or become certified.
• You will enjoy 3 weeks of paid time off and flexible working hours, with the requirement of only a stable internet connection.
• Pythian provides all the equipment you need to work from home, including a laptop with your choice of OS, and a budget to personalize your work environment.
• You will have the opportunity to blog during work hours and take a day off to volunteer for your favorite charity.