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Craft.co

Machine Learning Engineer

Reposted 20 Days Ago
Remote
160K-160K Annually
Mid level
Remote
160K-160K Annually
Mid level
As a Machine Learning Engineer at Craft, you'll manage end-to-end ML projects, integrating solutions with data pipelines, and championing MLOps within the team. Your role involves collaborating with engineers and stakeholders, designing maintainable software, and staying updated on ML trends, leveraging your production experience in ML models and anomaly detection.
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About Craft:

Craft is the leader in supplier risk intelligence, enabling enterprises to discover, evaluate, and continuously monitor their suppliers at scale. Our unique, proprietary data platform tracks real-time signals on millions of companies globally, delivering best-in-class monitoring and insight into global supply chains. Our customers include Fortune 500 companies, government agencies, SMEs, and global service platforms. Through our configurable Software-as-a-Service portal, our customers can monitor any company they work with and execute critical actions in real-time. We’ve developed distribution partnerships with some of the largest integrators and software platforms globally.

We are a post-Series B high-growth technology company backed by top-tier investors in Silicon Valley and Europe, headquartered in San Francisco with hubs in Seattle and London. We support remote and hybrid work, with team members across North America, Canada, and Europe.

We're looking for innovative and driven people passionate about building the future of Enterprise Intelligence to join our growing team!

About the Role:

Craft is looking for an experienced and motivated Machine Learning Engineer to join a team responsible for a key product within the organization. As a core member of this team you will have a great say in how solutions are engineered and delivered.

Craft gives engineers a lot of responsibility, which is matched by our investment in their growth and development. We are growing quickly, and the only limits to your future growth with Craft are your dedication and abilities.

The team has members in the US and Poland. This is a remote role, but we have a strong preference for candidates based in Eastern or Central time zones due to the current team members’ time zones.

What You'll Do:

  • Managing and developing end-to-end data science and machine learning projects, from research and data exploration to model development, validation, deployment, and optimization, such as entity resolution, anomaly detection, and agentic AI workflows

  • Determining the right tool for a job - whether that’s utilizing a LLM, developing a new model, using a simple heuristic or a combination of the above.

  • Integrating ML solutions with our data pipelines (Batch & Streaming)

  • Helping to implement and champion an MLOps solution to be used within the company.

  • Designing software that is easily testable and maintainable.

  • Working with Full-Stack, Data, and DevOps Engineers to ensure smooth delivery of new features.

  • Building strong partnerships with business stakeholders and product teams to understand key challenges, define objectives, and translate business needs into data science solutions that drive measurable impact and align with strategic goals

  • Keeping track of emerging technologies & trends in the Machine Learning world, incorporating latest research and tools at Craft.

Who You Are:

  • Production experience with creating and maintaining Machine Learning models. We expect you to be familiar with the entirety of ML Lifecycle and able to implement it by yourself.

  • Experience in identifying anomalies across various data domains, including change point detection, time series anomaly analysis, and unsupervised outlier detection, to uncover irregular patterns, and enhance predictive monitoring.

  • Robust experience using NLP solutions for unstructured data processing, along with a good sense of possibilities and limitations.

  • 3+ years of experience in Python, including PyTorch or other major data science libraries.

  • Experience with data science and software engineering - familiarity with clean code, unit testing and design patterns.

  • Experience with cloud services - preferably AWS and Databricks.

  • Self-starter who likes to take initiative.

  • Experience with at least a part of our technology stack: Python, Polars, Pandas, Pytorch, Pandas, spaCy, transformers, AWS, Sagemaker, S3, Batch, Athena, Lambda, Kinesis, Kafka, RDS/Aurora Postgres, DynamoDB, Neptune, OpenSearch, Glue, Athena, Airflow, Terraform

  • Experience with MLOps tools and best practices

What We Offer:

  • Competitive salary starting at $160,000 USD/ year. This starting number can be increased based on levels of expertise, location, cost of living, taxes, market experience, etc.

  • Equity at a well-funded, fast-growing startup

  • Unlimited vacation time so you can take what you need, when you need it

  • 99% covered Health + Dental + Vision insurance for employees and dependents

  • 401K through Empower with options to invest how you want it

A Note to Candidates:

We are an equal opportunity employer who values and encourages diversity, equity and belonging at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, caste, or disability status.

Don’t meet every requirement? Studies have shown that women, communities of color and historically underrepresented talent are less likely to apply to jobs unless they meet every single qualification. At Craft, we are dedicated to building a diverse, inclusive and authentic workplace, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we strongly encourage you to apply. You may be just the right candidate for this or other roles!


#BI-Remote

Top Skills

Airflow
Athena
AWS
Databricks
DynamoDB
Glue
Kafka
Kinesis
Lambda
Neptune
Opensearch
Pandas
Python
PyTorch
Rds/Aurora Postgres
S3
Sagemaker
Spacy
Terraform
Transformers

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