Forward Deployed Engineer
Chalk· startup· Computer Software· Oct 17, 2022 · 49mo agoPosted 1,471 days ago
NY / SF
In office
Full-time
Mid
$170K–$280K
2+ years exp
Before you apply
Ghost Signal:
Open since October 17, 2022 — 1,471 days, and still accepting applications.
Job description
About Chalk
Chalk (chalk.ai chalk.ai) is the platform for production AI. Trusted by enterprises including Whatnot, Grindr, Mission Lane, Turo, and Apartment List, Chalk brings together context, runtime, and learning for agents and models. Chalk’s Context Engine delivers live context by querying data across warehouses, databases, streams, and APIs, straight from the source. Chalk’s runtime powers agents and models with infrastructure and governed access to LLMs and tools. Together, these capabilities help teams build AI that understands their business, continuously improves, and runs reliably in production. We've recently raised a $50 million Series A, led by Felicis. Learn more at chalk.ai chalk.ai.
About the role
You are an exceptional Software Engineer who wants to work directly alongside the people using what you build. As a Forward Deployed Engineer, you will be embedded with our customers' data engineering, data science, and machine learning teams and write code that connects Chalk to their unique infrastructure and use cases. As the subject matter expert in the room, you will work with these data teams to build efficient ML and AI systems. When a customer needs something that Chalk doesn't do yet, you will prove out that new capability and personally build the first version into our platform, where it becomes available to every customer.
Your work will power use cases like cancer detection, fraud prevention, and product recommendation. This is your opportunity to join us in-person as an early employee and make a significant impact at a high growth start-up.
We're in the office 5 days a week. When unavoidable conflicts come up, we’re flexible. This is not a hybrid role. Traveling to customer sites is rare since you support teams from multiple customers while working in our office.
What you will do
- Write code across the entire code base to implement Chalk technology for Chalk customers and prospects. You will become familiar with Chalk infrastructure and find the best way to integrate and implement them in different environments
- Discover customer's needs and then design, implement, and ship new features for customers
- Work closely with our Engineering and Sales teams
- Act as the primary technical point of contact pre-sales and post-sales (when we are onboarding a new customer or supporting an existing one)
- Recommend new products to customers as their business evolves
- Help interview and grow the Engineering team
What we’re looking for
- Technical background including experience writing software or building ML models
- 2+ years experience of professional backend software engineering experience
- Proficient in Python, SQL
- Ability to collaborate effectively in teams of technical and non-technical individuals
- Excellent written and verbal communication, problem-solving, storytelling, and analytical skills
- Experience working closely with sales teams and customers is a plus.
- Bachelor's degree in Computer Science or equivalent
Bonus points
- Previous experience working with ML/data products or services
- Understanding of Machine Learning Ops/Infrastructure
- Previous experience as a forward-deployed engineer in a high-growth startup focusing on Machine Learning
Compensation
Chalk offers early team members a generous salary + equity package based on experience and competitive benefits.
Actual compensation awarded to successful candidates will be based on several factors, including but not limited to: market, location, scope of the position and individual qualifications objectively assessed during the interview process.
Our comprehensive total package plays a major role in how we recognize individuals for the impact they will have on Chalk’s growth and us achieving our goals.
Application prep
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Keywords to mirror
aimachine learningmlpythonsql
- Platform
- ashby
- Effort
- quick