AI/ML Engineer

Job Summary

As an AI / ML Engineer, you will be a contributor to the design, development, and implementation of Artificial Intelligence and Machine Learning solutions. Your primary focus will be on developing, implementing, and maintaining robust, scalable, and reliable AI/ML pipelines, with an emphasis on integrating and optimizing models, including Large Language Models (LLMs) and Generative AI technologies, into client and internal products. Your role requires a deep knowledge of ML engineering best practices and the AI ecosystem, coordinating with data scientists and software engineering teams.

Responsibilities

• Develop, deploy, and maintain robust AI and machine learning pipelines for internal and client-driven projects.
• Deploy, manage, and scale AI models, including pre-trained models (e.g., LLMs) and custom ML models, into production environments.
• Work with data scientists to implement model prototypes into scalable, production-ready AI systems.
• Optimize and tune model performance, latency, and cost-efficiency on cloud platforms.
• Integrate AI/ML solutions with major cloud platforms (AWS, GCP, Azure) and utilize containerization technologies (Docker, Kubernetes) for consistent deployment.
• Apply standard MLOps practices, including continuous integration/continuous delivery (CI/CD), model versioning, monitoring, and maintenance systems.
• Coordinate with software engineering teams to ensure seamless integration of AI capabilities into applications and user workflows.
• Stay up to date with advancements in AI/ML technologies, Generative AI, and MLOps deployment strategies.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, or a related quantitative field.
• 4 to 5 years of progressive experience in machine learning engineering, software development with an ML/AI focus, or a related role.
• Strong programming skills in Python and proficiency in ML/AI frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Hands-on experience in deploying and working with pre-trained models, such as Large Language Models (LLMs) or similar Generative AI technologies, into production environments.
• Solid experience with cloud platforms (AWS, GCP, Azure) and container orchestration using Docker and Kubernetes.
• In-depth knowledge of Data Engineering principles, ETL/ELT processes, and version control systems (e.g., Git).
• Experience in orchestrating Machine Learning pipelines using open-source tools like Kubeflow or managed cloud services.
• Experience in building and optimizing scalable AI/ML systems.
• Familiarity with MLOps best practices, including model monitoring, logging, and CI/CD pipelines for AI assets.
• Strong communication and teamwork skills, with an ability to work effectively across cross-functional teams including solution architects and data scientists.

What you will receive

• Love your work/life balance: Flexibly work remotely from your home, there's no daily travel requirement to an office! All you need is a stable internet connection.
• Love your coworkers: Collaborate with some of the best and brightest in the industry!
• Love your development: Hone your skills or learn new ones with our substantial training allowance; participate in professional development days, attend training, become certified, whatever you like!
• Love your workspace: We give you all the equipment you need to work from home including a laptop with your choice of OS, and an annual budget to personalize your work environment!
• Love yourself: Pythian cares about the health and well-being of our team. You will have an annual wellness budget to make yourself a priority (use it on gym memberships, massages, fitness and more). Additionally, you will receive a generous amount of paid vacation and sick days, as well as a day off to volunteer for your favorite charity.

Hiring Disclaimer

• The successful applicant will need to fulfill the requirements necessary to obtain a background check.
• Accommodations are available upon request for candidates taking part in any aspect of the selection process.

Disclaimer: This job posting and Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.