Machine Learning Engineer

Sunnydata
Argentina
RemoteCareer-pivot friendly

Who this role is best for

Candidates with experience in deploying machine learning models and strong communication skills will find this role impactful.

Best fit for

  • Individuals with a background in statistics and a strong grasp of cloud-based data solutions and MLOps practices.
    — “Strong background in statistics, A/B testing, and machine learning algorithms.”
  • Candidates who thrive in cross-functional environments and can mentor junior data scientists.
    — “Mentor junior data scientists and contribute to best practices in model development and operationalization.”

Things to consider

  • The role requires a minimum of 4 years of experience, which may be a barrier for less experienced candidates.
    — “4+ years of experience in data science or machine learning roles.”
  • Candidates must be proficient in Python and SQL, and familiarity with big data tools is preferred.
    — “Proficient in Python (pandas, scikit-learn, PyTorch or TensorFlow) and SQL.”

How to stand out

  • Highlight your experience with deploying models in production environments and your leadership in mentoring junior staff.
    — “Experience building and deploying models in production environments.”
  • Showcase your ability to work with large, complex datasets and build predictive analytics pipelines.
    — “Work with large, complex datasets to extract valuable insights and build predictive analytics pipelines.”
  • Demonstrate your expertise in MLOps practices and cloud-based tools like Airflow and SageMaker Pipelines.
    — “Familiarity with MLOps practices and tools (e.g., MLflow, SageMaker Pipelines, Airflow).”
  • Emphasize your statistical modeling skills and how you have used them to solve business challenges.
    — “Translate business challenges into data-driven solutions using statistical modeling and machine learning techniques.”
  • Demonstrate your ability to communicate findings and strategic recommendations to stakeholders and leadership.
    — “Communicate findings and strategic recommendations to stakeholders and executive leadership.”
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Scalable machine learning solutions
  • Actionable insights
  • Improved business outcomes
Typical background
Machine Learning EngineerData ScientistData Engineer

Skills & requirements

Required

Machine LearningPredictive ModelingData EngineeringCloud ServicesCI/CDMlopsModel DeploymentData Pipelines

Preferred

Big Data ToolsContainerizationServerless Architecture

About the role

Original posting from Sunnydata via Ashby

At SunnyData, our mission is to help customers build a highly scalable architecture, robust data engineering pipelines, easy data consumption layers and more importantly build ML and AI applications to power their business and drive outstanding business outcomes. As a Machine Learning Engineer you will lead complex data projects, develop predictive models, and deploy scalable machine learning solutions. You will work cross-functionally with engineering, product, and analytics teams to derive actionable insights and influence key business decisions.

The Impact You Will Have

  • Lead the design, development, and deployment of machine learning models.
  • Work with large, complex datasets to extract valuable insights and build predictive analytics pipelines.
  • Collaborate with data engineers to architect and optimize cloud-based data solutions.
  • Translate business challenges into data-driven solutions using statistical modeling and machine learning techniques.
  • Automate data workflows and model deployment processes using cloud services and CI/CD tools.
  • Mentor junior data scientists and contribute to best practices in model development and operationalization.
  • Communicate findings and strategic recommendations to stakeholders and executive leadership.

What We Look For

  • 4+ years of experience in data science or machine learning roles.
  • Proficient in Python (pandas, scikit-learn, PyTorch or TensorFlow) and SQL.
  • Strong background in statistics, A/B testing, and machine learning algorithms.
  • Experience building and deploying models in production environments.
  • Familiarity with MLOps practices and tools (e.g., MLflow, SageMaker Pipelines, Airflow).
  • Excellent communication and leadership skills.

PREFERRED QUALIFICATIONS

  • Experience with big data tools (Spark, EMR).
  • Familiarity with containerization (Docker, ECS, EKS) and serverless architecture.

Education

  • Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or a related field is preferred.

Our Commitment to Diversity and Inclusion:

SunnyData is dedicated to building a workforce that reflects the world around us. We are an equal opportunity employer committed to unbiased hiring practices. All qualified applicants will receive consideration for employment without regard to race, religion, gender identity, disability, veteran status, or any other protected characteristic.

Why Join SunnyData?

  • Innovative Environment: Work with cutting-edge technologies and industry leaders in data engineering and AI.
  • Customer Impact: Make a real difference in how businesses leverage data for strategic decision-making.
  • Career Growth: Opportunities for professional development and career advancement.
  • Collaborative Culture: Join a supportive team that values collaboration and knowledge sharing.

If you are passionate about data engineering and enjoy engaging with clients to solve their most challenging problems, we would love to hear from you. Apply today and become a key player in SunnyData's success story.

Source: Sunnydata careers (Ashby)

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