Applied ML Scientist

hackajob on-Demand is currently partnering with an AI startup company to help them hire the best talent. At on-demand, we match and speak with exceptional talent like you and provide insights into the problem they are looking to solve and the interview process.

About Them

They aim to address the shortage of skilled labor in critical domains such as healthcare, by creating AI assistants that can perform tasks that typically require human-level intelligence.

They are looking for a motivated Applied ML Scientist to work with them on developing a leading edge LLM and knowledge-based systems.

About You

As an applied ML scientist, you may succeed in this role if you:

• Possess a minimum of 5 years of experience in machine learning and engineering, with a focus on product-oriented companies.
• Are proficient in Python for both machine learning and backend development within production environments.
• Are enthusiastic about keeping abreast of the rapid advancements in AI and LLM technologies.
• Showcase humility, a collaborative demeanor, and a readiness to aid colleagues to foster team achievements.
• Are comfortable taking ownership within a dynamic and fast-paced startup environment.

Additionally, the following would be considered advantageous:

• Previous experience in an early-stage startup.
• Familiarity with healthcare data and electronic health records.

About the Role

The applied ML scientist will work closely with the founding team to develop the core product offering and helping build out the team.

The work will include:

1. Experimenting with foundational LLMs and advanced prompting techniques (e.g. React) and integrating these with external data and knowledge bases.

2. Model fine-tuning and deployment as well as optimising for performance vs latency.

3. Implementing monitoring and guardrails and defining best practices for leveraging generative AI in production.

4. Create reproducible experimentation pipelines to benchmark their LLM-based agents and facilitate rapid iteration.

5. Collaborate closely with cross-functional teams including engineers, clinicians, and product owners to understand business requirements and translate them into technical solutions.