Machina

Data Scientist – AI/ML

Machina

full-time

Posted on:

Location Type: Remote

Location: Remote • 🇺🇸 United States

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Job Level

Mid-LevelSenior

Tech Stack

AWSAzureCloudGoogle Cloud PlatformHadoopPandasPythonPyTorchScikit-LearnSparkTensorflow

About the role

  • Design, implement, and deploy machine learning models to optimize software build systems, including caching, task distribution, and execution workflows
  • Work with large datasets to identify patterns, anomalies, and insights that inform decisions for improving build processes and remote execution
  • Develop predictive models to optimize build times, cache hit rates, and system resource utilization
  • Conduct experiments to improve the efficiency of build systems through data-driven decisions, leveraging AI/ML techniques such as reinforcement learning and optimization
  • Collaborate with cross-functional teams (engineering, product, and operations) to translate business problems into AI/ML-driven solutions
  • Analyze customer usage data to identify opportunities for feature improvements and innovations within the NativeLink platform
  • Develop custom algorithms for performance monitoring, anomaly detection, and optimization of CI/CD pipelines
  • Build, test, and validate machine learning models using a variety of techniques, ensuring they are scalable, robust, and interpretable
  • Build and maintain data pipelines to support model training, testing, and deployment in production environments
  • Communicate findings and insights to both technical and non-technical stakeholders in a clear and actionable way

Requirements

  • 3+ years of experience as a Data Scientist, with a strong focus on AI and machine learning
  • Expertise in machine learning algorithms, data analysis, and statistical modeling techniques
  • Proficiency in Python, R, or other data science programming languages, with experience using libraries such as TensorFlow, PyTorch, Scikit-learn, and Pandas
  • Strong knowledge of deep learning, reinforcement learning, or other advanced AI techniques
  • Experience with large-scale data processing, including working with big data technologies (e.g., Spark, Hadoop)
  • Familiarity with cloud infrastructure (AWS, GCP, Azure) and deploying machine learning models in production
  • Strong understanding of data wrangling, feature engineering, and building predictive models
  • Experience with version control (Git) and working in collaborative environments
  • Excellent problem-solving skills and ability to generate actionable insights from data
  • Ability to communicate complex AI/ML concepts effectively to both technical and non-technical teams.
Benefits
  • Competitive salary and benefits package
  • Opportunities for career growth, professional development, and continuous learning

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
machine learningdata analysisstatistical modelingpredictive modelingdata wranglingfeature engineeringdeep learningreinforcement learningalgorithm developmentanomaly detection
Soft skills
problem-solvingcommunicationcollaborationdata-driven decision makinginsight generation