Machine Learning Engineer

Sunnydata

Uruguay

Hybrid

Who this role is best for

Candidates with production ML experience and collaboration skills will find this role impactful.

Best fit for

Candidates with 4+ years of ML experience and a track record of deploying models in production
— “Experience building and deploying models in production environments.”
Professionals skilled in Python, SQL, and MLOps tools who enjoy working with large datasets
— “Proficient in Python (pandas, scikit-learn, PyTorch or TensorFlow) and SQL.”

Things to consider

The role demands a strong background in statistics and machine learning algorithms
— “Strong background in statistics, A/B testing, and machine learning algorithms.”

How to stand out

Highlight experience with cloud-based data solutions and MLOps in your resume and interviews
— “Collaborate with data engineers to architect and optimize cloud-based data solutions.”
Emphasize your ability to translate business problems into data-driven strategies
— “Translate business challenges into data-driven solutions using statistical modeling and machine learning techniques.”
Showcase your leadership and mentoring experience, especially with junior data scientists
— “Mentor junior data scientists and contribute to best practices in model development and operationalization.”
Demonstrate your skills in automating data workflows and deploying models using CI/CD tools
— “Automate data workflows and model deployment processes using cloud services and CI/CD tools.”

Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

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

What success looks like

deployed machine learning models
extracted valuable insights
mentored junior data scientists

Typical background

4+ years of experience in data science or machine learning roles

Skills & requirements

Required

Machine LearningData EngineeringPredictive ModelingCloud Services

Preferred

Big Data ToolsContainerizationServerless Architecture

Stack & domain

PythonPandasscikit-learnPyTorchTensorFlowSQLStatisticsA/B TestingMachine Learning AlgorithmsBig Data ToolsContainerizationServerless ArchitectureCommunicationLeadershipProblem SolvingTeamworkData EngineeringAI

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)