Principal Platform Engineer – Data Ops Engineer
DIRECTV
AirflowApacheAWSJavaScriptJenkinsJMeterPySparkPythonShell ScriptingSparkSplunk
Senior Machine Learning Platform Engineer
Dave
full-time
Posted on:
Location Type: Remote
Location: Remote • 🇺🇸 United States
Visit company websiteSalary
💰 $138,000 - $222,000 per year
Job Level
Senior
Tech Stack
AirflowAWSCloudDistributed SystemsGoogle Cloud PlatformPythonPyTorchScikit-LearnSparkSQLTensorflow
About the role
- Drives technical decisions for tasks, choosing solutions that are scalable, easily testable, and reduce tech debt.
- Influences the team to maintain high standards for code quality and system reliability through exemplary code and constructive, insightful code reviews.
- Uses code reviews as an opportunity to coach and mentor other engineers on the team.
- Exhibits a deep understanding of the Machine Learning Platform, its architecture, and codebase.
- Proactively identifies and communicates technical risks and issues within our systems.
- Provides reliable engineering estimates with clear assumptions for complex projects and epics.
- Leads technical design discussions, collaborating with other engineers and stakeholders to evaluate trade-offs between different solutions. You seek to deeply understand the "why" behind product and roadmap decisions.
- Actively works to improve team processes to boost quality and velocity.
- Proactively communicates project status, dependencies, and relevant information across squads.
- Helps onboard new team members, getting them up to speed on our systems and best practices.
- Participates in interviewing and helps us raise the bar by providing thoughtful, well-calibrated feedback on candidates.
Requirements
- BS in Computer Science, related technical field or equivalent practical experience. MS or PhD in Computer Science or Machine Learning is a plus.
- 5+ years of professional software development experience, with a focus on backend or infrastructure engineering. Experience building or operating large-scale, high-availability distributed systems is a plus.
- Deep expertise in Python and familiarity with the end-to-end Machine Learning lifecycle and common Machine Learning frameworks (e.g., Scikit-learn, XGBoost, PyTorch, TensorFlow). Proficiency in another programming language is a plus.
- Proven experience building scalable, high-performing distributed systems in a cloud environment (GCP, AWS).
- Experience with workflow orchestration tools (e.g., Airflow) and large-scale data processing frameworks (e.g., Spark, Beam).
- Proficiency in common database query languages and technologies (SQL required; Snowflake, non-relational query languages optional).
- Experience leading complex technical projects from ideation to production.
- A strong ability to collaborate and a penchant for architecting maintainable, reliable, and well-documented solutions.
- Experience with MLOps, productionizing machine learning models, or building data-intensive applications is a plus.
Benefits
- Opportunity to tackle tough challenges, learn and grow from fellow top talent, and help millions of people reach their personal financial goals
- Flexible hours and virtual first work culture with a home office stipend
- Premium Medical, Dental, and Vision Insurance plans
- Generous paid parental and caregiver leave
- 401(k) savings plan with matching contributions
- Financial advisor and financial wellness support
- Flexible PTO and generous company holidays, including Juneteenth and Winter Break
- All-company in-person events once or twice a year and virtual events throughout to connect with your team members and leadership team
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
PythonMachine LearningScikit-learnXGBoostPyTorchTensorFlowSQLAirflowSparkBeam
Soft skills
code qualitysystem reliabilitycoachingmentoringcommunicationcollaborationproject managementprocess improvementfeedbackleadership
Certifications
BS in Computer ScienceMS in Computer SciencePhD in Computer ScienceMachine Learning
