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Machine Learning Engineer

extra holidays - extra parental leave - fully flexible

Remote:

Full Remote

Contract:

Full time

Salary:

150 - 180K yearly

Experience:

Mid-level (2-5 years)

Work from:

United States

Offer summary

Qualifications:

Master’s degree or equivalent experience (2+ years), Solid understanding of machine learning fundamentals, High comfort level in Python or similar language, Familiarity with ML stack and data analysis, Ability to collaborate with technical partners.

Key responsabilities:

Generate insights into customer behavior
Work with data engineers for additional data collection
Create meaningful machine-learning features
Build and deploy machine learning models

Movable Ink Information Technology & Services SME https://movableink.com/

501 - 1000 Employees

See more Movable Ink offers

Job description

Movable Ink scales content personalization for marketers through data-activated content generation and AI decisioning. The world’s most innovative brands rely on Movable Ink to maximize revenue, simplify workflow and boost marketing agility. Headquartered in New York City with close to 600 employees, Movable Ink serves its global client base with operations throughout North America, Central America, Europe, Australia, and Japan.

As a machine learning engineer, you will be part of our Applied AI and Machine Learning team. You will work alongside other scientists and engineers in a collaborative environment, contributing features and machine learning models to our core recommender systems and our DaVinci Personalization product. This is an opportunity to work end-to-end on a large-scale machine-learning system that touches millions of customers, and a chance to continuously learn and help improve our solution as the field evolves.

Responsibilities:

Generate insights into customer behavior and derive modeling ideas for improving our content recommender system
Work with data engineers to define what additional customer data we might want to collect and help make it available in a format suitable for modeling purposes
Create meaningful machine-learning features that improve our content recommender’s performance measured through offline metrics and online a/b tests
Build machine learning models and deploy them as part of our recommender system

Qualifications:

Master’s degree or equivalent experience (2+ years) in a relevant field or industry
Solid understanding of machine learning fundamentals
High comfort level in Python or other programming language
Familiarity with an ML stack such as typical scientific Python libraries (pandas, numpy, sklearn, xgboost) or deep learning frameworks (we use Pytorch)
Familiarity with data analysis through SQL or a big-data processing framework such as Spark
Ability to collaborate with technical partners – you’ll be working closely with other teams to determine requirements for your work and to make design decisions that affect our stack
The idea of writing and deploying production code, and getting real-world feedback on your models excites you
A desire to always be learning and contributing to a collaborative environment

The base pay range for this position is $150,000 - $180,000 USD/year. The base pay offered may vary depending on job-related knowledge, skills, and experience. Stock options and other incentive pay may be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits, depending on the position ultimately offered.

Studies have shown that women, communities of color, and historically underrepresented people are less likely to apply to jobs unless they meet every single qualification. We are committed to building a diverse and inclusive culture where all Inkers can thrive. If you’re excited about the role but don’t meet all of the abovementioned qualifications, we encourage you to apply. Our differences bring a breadth of knowledge and perspectives that makes us collectively stronger.

We welcome and employ people regardless of race, color, gender identity or expression, religion, genetic information, parental or pregnancy status, national origin, sexual orientation, age, citizenship, marital status, ethnicity, family or marital status, physical and mental ability, political affiliation, disability, Veteran status, or other protected characteristics. We are proud to be an equal opportunity employer.