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Principal Software Engineer, Machine Learning
AI in this role
Build, scale, and operate production-grade machine learning systems powering real-time personalization for a marketing platform.
About the Role
Our Machine Learning Engineering team powers personalized experiences for hundreds of millions of customers across thousands of brands. As a Senior Machine Learning Engineer, you will play a critical role in building, scaling, and operating production-grade ML systems that drive real-time personalization across the Attentive platform.
You will operate with a high degree of ownership, partner closely with Product and Engineering, and help raise the technical bar across our ML systems in a fast-paced, high-impact environment.What You’ll Accomplish
- You have a proven track record of building systems that maintain a high bar of quality
- You deeply loathe regressions and take proactive steps to protect against them through a variety of testing techniques
- You are a collaborator, technical leader, and a great communicator
- You are constantly improving the quality of the project you are working on, both via direct contributions as well as long-term advocacy for larger-scale changes
- You are enthusiastic about the high impact, fast-paced work environment of an late-stage startup
- 10+ years experience is ideal
Your Expertise
- You have worked professionally building systems for 10+ years with experience on a single system long enough to see the consequences of your decisions
- Experience with TensorFlow/Pytorch, xgboost, pandas, matplotlib, SQL, Spark or similar tools
- You have proficiency or experience with Python
- You have extensive experience using machine learning and data analysis, or similar, to build scalable systems and data-driven products, working with cross-functional teams
- You have a proven track record of building scalable, efficient, automated processes for large-scale data analyses, model development, model validation, and model implementation from modern research
- You have led cross-functional machine learning projects across teams
What We Use
- Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS
- Infrastructure tooling includes Istio, Datadog, Terraform, CloudFlare, and Helm
- Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, Kinesis, AirFlow, Postgres, Planetscale, and Redis, hosted via AWS
- Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright
- Our automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas
You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.
For US based applicants:
- The US base salary range for this full-time position is $350,000 - $430,000 annually + equity + benefits
- Our salary ranges are determined by role, level and location
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Attentive Company Values Default to Action - Move swiftly and with purpose Be One Unstoppable Team - Rally as each other’s champions Champion the Customer - Our success is defined by our customers' success Act Like an Owner - Take responsibility for Attentive’s success Learn more about AWAKE, Attentive’s collective of employee resource groups. If you do not meet all the requirements listed here, we still encourage you to apply! No job description is perfect, and we may also have another opportunity that closely matches your skills and experience. At Attentive, we know that our Company's strength lies in the diversity of our employees. Attentive is an Equal Opportunity Employer and we welcome applicants from all backgrounds. Our policy is to provide equal employment opportunities for all employees, applicants and covered individuals regardless of protected characteristics. We prioritize and maintain a fair, inclusive and equitable workplace free from discrimination, harassment, and retaliation. Attentive is also committed to providing reasonable accommodations for candidates with disabilities. If you need any assistance or reasonable accommodations, please let your recruiter know.How we rate this
Principal Software Engineer, Machine Learning at Attentive rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in software engineer jobs at this level
Questions you could be asked
- Tell me about a project where machine engineering was part of your work. What did you do?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where distributed systems was part of your work. What did you do?
- Tell me about a project where software engineering was part of your work. What did you do?
- Walk me through how you've used Hugging Face in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Machine Engineering, Machine learning, Distributed Systems, Software Engineering, and Hugging Face. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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