Senior ML Systems Engineer

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior ML Systems Engineer in the United States.

This role focuses on designing, building, and maintaining large-scale machine learning data platforms in a hybrid work environment. You will be responsible for developing robust, scalable, and cost-efficient ML data processing and serving systems, supporting feature engineering, model training, validation, deployment, and monitoring. The position involves collaborating across teams to deliver high-throughput, low-latency solutions, optimizing cloud infrastructure, and ensuring operational excellence. Ideal candidates are passionate about cutting-edge ML infrastructure, have strong experience with distributed systems such as Beam and Spark, and enjoy mentoring and guiding engineering teams. This is an opportunity to influence the evolution of enterprise ML platforms while contributing to impactful technology initiatives.

Accountabilities:

• Lead development, optimization, and production deployment of next-generation ML data processing platforms using Beam, Spark, and cloud technologies
• Build self-serve capabilities to enable teams to adopt ML data processing and mining tools efficiently
• Design, implement, and test scalable distributed data systems in the cloud while championing engineering best practices
• Own technical projects from start to finish, contribute to the product roadmap, and make major technical decisions and tradeoffs
• Collaborate with partner teams to meet cross-organizational goals and satisfy broad requirements
• Conduct technical interviews, mentor junior engineers and interns, and support onboarding processes
• Ensure robust, spike-resistant, and cost-efficient solutions for high-throughput, low-latency data serving systems
• Participate in planning, code reviews, and design discussions to continuously improve team outputs
  
  
  

Requirements

• 7+ years of professional experience in engineering, including large-scale ML systems
• BA or BS in Computer Science, Electrical Engineering, Mathematics, Physics, or a related field, or equivalent practical experience
• Experience building ML data processing platforms using Beam, Spark, or similar ecosystems
• Proven ability to optimize data processing clusters for cost efficiency and performance
• Experience building end-to-end ML model lifecycle systems, including feature engineering, model training, validation, deployment, and monitoring
• Strong programming skills in Python, Java, Scala, or similar languages for cloud infrastructure
• Experience with distributed, high-throughput, low-latency systems
• Excellent problem-solving, attention to detail, and collaboration skills
• Passion for impactful technology and innovative ML solutions
• Preferred: experience with SQL for analytics, building petabyte-scale systems, or relevant publications
  
  
  

Benefits

• Competitive base salary range: $134,000 - $241,900, with potential performance-based incentives
• Health, dental, and vision coverage, including flexible spending accounts and HSA options
• Retirement savings plan and employer contributions
• Paid vacation, holidays, and tuition assistance programs
• Relocation benefits may be available depending on location
• Opportunities for professional growth, mentorship, and continuous learning
• Hybrid work arrangement with office locations in Austin, TX, Mountain View, CA, or Greater Seattle Area
  
  
  

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.

🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.

📊 It compares your profile to the job's core requirements and past success factors to determine your match score.

🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role.

🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role.

Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.

Thank you for your interest!