Applied AI Engineer
Tandem
Taro Hiring Bonus Eligible
Receive a cash bonus of up to $15,000 when you successfully land this role. You can view your bonus here.
Job Description
Tandem is building the world's largest network of doctors, patients, and first-party data, applying AI to every step of bringing new therapies to market. Their first product ensures people get life-changing therapeutics as quickly and cheaply as possible. As an Applied AI Engineer, you will work on real production use cases of LLMs and other ML techniques to solve business problems and create groundbreaking AI applications. You will develop a deep understanding of Tandem's product and business to drive impact cross-functionally and independently.
Responsibilities include scoping AI augmentation and automation projects, driving zero-to-one product development, staying on top of emerging AI methods, establishing research strategies, and productionizing AI functionality. You will also participate actively in client engagements and develop engineering processes to support faster AI product development. The tech stack includes Python, React, TypeScript, PostgreSQL, and Kubernetes.
This role offers a high level of autonomy and responsibility, with opportunities to learn and drive company growth and accelerate your career. Tandem offers competitive equity and visa sponsorship.
Responsibilities
- Scope and spearhead AI augmentation and automation projects across our product surface area, including: _Unintuitive classifications, Data extraction and summarization, Precise content generation, Reference-based search and question answering, Process outcome prediction, Probabilistic triggering of workflows, and Multimodal model-powered bots_
- Drive zero-to-one product development from conceptualization through production, collaborating with our go-to-market and operations teams
- Stay on top of emerging AI methods and drive decisions around which models and techniques we use, including where we fine-tune and train models
- Establish research strategies for various AI methods, including experimentation and evaluation protocols that control for both accuracy and consistency
- Prototype and productionize AI functionality and agents, incorporating real-world feedback to refine them
- Participate actively in client engagements, working directly with customers to understand requirements and deliver innovative solutions
- Develop engineering process, tools, and systems to support faster AI product development (e.g., build a one-click eval system) and scaling (e.g., model invocation efficiency)
- Work closely with the rest of our team and CEO to make business decisions as we balance speed of growth and long-term profitability
- Decipher and automate complex, branching workflows for insurance coverage, affordability programs, and fulfillment
- Combining AI/ML approaches to achieve high precision document classification, unstructured data extraction, and reference-based question answering
- Automating multi-step, path-dependent processes, using a combination of RPA/scraping approaches to navigate and operate third-party platforms
- Build a state machine that drives system decisions and handles failure modes across a set of processes that are technically independent but practically intertwined
- Scale across a growing range of drug classes, patient populations, and provider markets
- Make our data and ML pipelines robust to variation and inconsistency in input data formats (e.g., clinical documentation structure and style)
- Leverage empirical data to build and continuously update our understanding of opaque external systems (e.g., insurance company policies)
- Create consumer-grade experiences for patients, physicians, and other users that incorporate intuitive AI-powered workflows
- Use our network to help biopharma partners accelerate drug development, launch, and access
- Translate large volumes of heterogeneous data into reliable insights, informing decisions like clinical indication selection, launch markets, and insurer negotiations
- Develop predictive and simulation models to forecast outcomes such as clinical trial site performance, drug adoption rates, and the impact of rebates/subsidies
- Use real-time data and direct engagement channels to enroll criteria-matching patients and physicians in clinical studies and access programs
Requirements
- 0 - 15 years of experience as a AI engineer, ML engineer, or ML research engineer at a high-quality company (i.e. Scale AI, Square, Stripe) or early stage startups
Benefits
- Equity
- Visa sponsorship available
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