Machine Learning Applied Scientist, OfferFit

Reinforcement Learning

$120-180k

+Eligibility for additional bonus ranging $15,000-$22,000

Kubernetes

TypeScript

GCP

JavaScript

Python

Node.js

Postgres

Airflow

Terraform

Vue.js

Spark

BigQuery

FastAPI

Junior, Mid and Senior level

Remote in Canada, EU, UK, US

AI platform making A/B testing obsolete

Open for applications

AI platform making A/B testing obsolete

21-100 employees

B2BArtificial IntelligenceEnterpriseMarketingMachine LearningSaaSAutomation

Open for applications

$120-180k

+Eligibility for additional bonus ranging $15,000-$22,000

Kubernetes

TypeScript

GCP

JavaScript

Python

Node.js

Postgres

Airflow

Terraform

Vue.js

Spark

BigQuery

FastAPI

Junior, Mid and Senior level

Remote in Canada, EU, UK, US

21-100 employees

B2BArtificial IntelligenceEnterpriseMarketingMachine LearningSaaSAutomation

Company mission

To accelerate the creation of knowledge - because with more and better knowledge, there’s no telling how substantially life can improve in the coming generations.

Job

Company

Role

Who you are

Exceptional coder: you have experience on writing clean, well-designed, versioned code; you care about good coding practices and terse, testable APIs
Problem solver: you thrive on tackling complex, real-world challenges with novel ML approaches
Impact-driven: you're motivated by seeing your research translate into tangible business outcomes
Collaborative: You enjoy working closely with a team of driven individuals across multiple teams to get things done. You’re willing to both help and ask for help
Structured and organized: you can structure a plan, align stakeholders, and see it through to execution
Clear communicator: you are able to express yourself clearly and persuasively, both in writing and speech
Ph.D. in Computer Science, Machine Learning, or a related field with a focus on Reinforcement Learning. MS with professional experience with RL is fine too

What the job involves

Our team is growing! We’re looking for an RL researcher or practitioner who will apply reinforced learning to solve real-world customer communication challenges
In this role, you'll work closely with the CTO and Engineering team to improve sample efficiency, test credit assignment and attribution algorithms, investigate and improve our approach to action space featurization, reward shaping, combining RL with constrained optimization, and other interesting challenges
Currently, we use ensembles of contextual bandits to achieve high sample efficiency and coordination of decisions, and we’re constantly testing and implementing improvements
Improve RL algorithms to increase performance, sample efficiency, and robustness at scale
Develop and apply advanced diagnostic tools, including off-policy evaluation methods
Conduct research on state-of-the-art RL techniques and their applicability to marketing optimization
Implement better monitoring and observability tooling
Work closely with engineering teams to improve OfferFit’s platform and develop APIs for OfferFit ML components
Participate in customer implementations to gain insights into real-world use cases
Contribute to OfferFit’s product strategy and roadmap
Tech stack:
Data Science/Back End: Python ML ecosystem, Spark, BigQuery, FastAPI
Architecture/DevOps: Kubernetes, Airflow, Terraform, GCP
Web [not required for this role] : TypeScript, JavaScript, Vue.js and its ecosystem, Node.js, Strapi, PostgreSQL, HTML5, CSS3
We write well-tested, type-hinted, documented, modular code and use pre-commit hooks, CI/CD, and issue tracking for development

Our take

In the realm of digital marketing, traditional A/B testing is facing significant challenges in optimizing and personalizing communication strategies. The limitations of this approach, which is employed to measure the effectiveness of different messages among user groups, include scalability issues and the inability to continuously adapt to evolving user behaviors.

OfferFit addresses these industry challenges by leveraging machine learning to revolutionize digital marketing optimization. Unlike traditional A/B testing, OfferFit's approach involves algorithms trained through trial-and-error, akin to how humans learn. This method allows for ongoing adjustments, ensuring continuous optimization over time.

The recent closure of a successful funding round signals a bright future for OfferFit. This significant investment will be channeled into expanding the platform's research and development, and strengthening sales and marketing operations. As the company secures additional support and proves its value to large customers, it aims to solidify its position as a trailblazer in automated, personalized marketing at scale.

Steph

Company Specialist at Welcome to the Jungle

Company

Funding (2 rounds)

Nov 2023

$25m

SERIES B

Nov 2021

$14m

SERIES A

Total funding: $39m

Company benefits

Generous PTO policy: Starting at 25 days PTO per year
100% remote work environment: With flexible hours
Quarterly gatherings: Where we meet in person in different cities to work together, bond as a team, and celebrate our progress
Weekly team events: Lunch and learns, trivia, virtual escape rooms, town halls, and team health "barometer" meetings

Company HQ

Government Center, Boston, MA

Leadership

George Khachatryan

(CEO)

Previously co-founded the educational software for schools company, Reasoning Mind. They also worked as an Associate Partner at McKinsey & Company before co-founding OfferFit in 2020.

Victor Kostyuk

(CTO)

Previously worked at the Boston Consulting Group in multiple Data Scientist roles. Prior to that they worked at Reasoning Mind for over 6 years in multiple roles.

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