MLOps Engineer - 4 Day Week + Remote (India and Philippines)

October 15, 2024

Industry: Private

Employment Type:- Full Time

Work Hours:- 8 Hours

Locations:- USA

Full Job Description:-

Purpose of the role

We seek a self-sufficient MLOps Engineer with a deep understanding and hands-on experience in deploying Large Language Models (LLMs) into production. This role requires an individual who can independently handle the complexities of LLMs, from fine-tuning to integration with existing systems, while closely collaborating with the product and engineering teams to ensure seamless implementation and optimisation.

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Team

Join a team of forward-thinking software engineers and product strategists. While you will be working autonomously on the deployment and management of LLMs, coordination with our Product Management and Site Reliability Engineering (SRE) teams will be essential for integrating these models into our broader platform.

Your top 3 objectives

Effective Deployment of LLMs: Successfully deploy LLMs into production, ensuring they align with our business needs and human values.
Optimise LLM Performance: Apply techniques such as reinforcement learning, instruction fine-tuning, and model optimization to enhance the performance and reliability of LLMs.
Integrate LLMs into Applications: Seamlessly integrate LLMs with external applications, enabling them to contribute effectively to our suite of products.

Your top 5 responsibilities

Collaborate Scope Definition: Engage with product team to define ML project use cases precisely, setting a clear direction for technical implementation.
Lifecycle Management: Oversee the ML project lifecycle stages, including model selection, prompt engineering, fine-tuning, evaluation, and alignment with human feedback.
Optimize and Deploy for Inference: Optimize LLMs for inference and deploy them into production, ensuring they meet the functional and performance criteria established during scoping.
Enhance Applications with LLMs: Work within the software development team to tailor LLMs to our unique application requirements, ensuring that the models effectively power and enhance our products' functionality and user experience.
Collaborate with the SRE Team: Work closely with the SRE team for the integration of LLMs into our cloud infrastructure, ensuring scalability and resilience.

Your Capabilities

As an MLOps Engineer focused on LLMs, you combine deep technical expertise with a proactive approach to problem-solving. You are adept at working independently yet understand the importance of aligning your work with broader team objectives.

Must-Have (The fundamentals)

Expertise in LLM Deployment: Extensive experience in deploying and managing Large Language Models, including all aspects of fine-tuning and integration.
Technical Proficiency: Strong skills in machine learning frameworks, cloud computing, and interacting with external applications.
Independent Problem-Solver: Ability to tackle challenges autonomously, applying innovative solutions to complex problems.
Continuous Learner: Commitment to staying abreast of the latest developments in LLMs and MLOps.

Nice to Have (If you don’t have it now you will after joining)

Advance Model Optimization Skills: Knowledge of advance model fine-tuning and optimization techniques.
Collaborative Approach: While working autonomously, the ability to effectively coordinate with other teams, like SRE, for seamless integration.
Community Engagement: Active participation in relevant tech communities to bring in new insights and best practices.

Shape isn’t the place for you if any of the following is true:

You want an easy, chilled-out role without much challenge
You like to be the smartest person in the room
You don’t like continuously receiving honest candid feedback
You prefer to do your own thing rather than work with a team

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