Frontera is hiring a Software Engineer - Machine Learning Platform

About the Role

Contribute to the design, implementation, and maintenance of a scalable and reliable machine learning platform, ensuring high performance and efficiency.

Responsibilities

• Design and implement scalable and reliable machine learning systems.
• Develop and maintain machine learning models and pipelines.
• Collaborate with data scientists and engineers to integrate machine learning models into production systems.
• Ensure the performance, quality, and scalability of machine learning solutions.
• Monitor and optimize machine learning models and infrastructure.
• Implement and maintain data processing and storage solutions.
• Develop and maintain APIs and microservices for machine learning applications.
• Contribute to the development of machine learning frameworks and tools.
• Implement and maintain CI/CD pipelines for machine learning models.
• Conduct code reviews and pair programming sessions to ensure code quality.
• Troubleshoot and resolve issues in machine learning systems.
• Document machine learning models, pipelines, and systems.
• Stay up-to-date with the latest developments in machine learning and related technologies.
• Collaborate with cross-functional teams to define, design, and ship new features.
• Work on improving the scalability and performance of machine learning models.
• Develop and maintain machine learning infrastructure.
• Implement and maintain monitoring and logging solutions for machine learning systems.
• Contribute to the development of machine learning best practices and standards.
• Participate in on-call rotations to ensure the availability and reliability of machine learning systems.
• Conduct performance testing and optimization of machine learning models.
• Develop and maintain machine learning dashboards and visualizations.
• Collaborate with product managers to define and prioritize machine learning projects.
• Work on improving the accuracy and efficiency of machine learning models.
• Develop and maintain machine learning training and deployment pipelines.

Nice to Have

• Master's degree in Computer Science, Engineering, or a related field.
• Experience with machine learning model serving and inference.
• Experience with machine learning model training and deployment at scale.
• Experience with machine learning model A/B testing and experimentation.
• Experience with machine learning model deployment in production environments.
• Experience with machine learning model deployment in cloud environments.
• Experience with machine learning model deployment in on-premises environments.
• Experience with machine learning model deployment in hybrid environments.
• Experience with machine learning model deployment in multi-cloud environments.
• Experience with machine learning model deployment in edge environments.
• Experience with machine learning model deployment in IoT environments.
• Experience with machine learning model deployment in mobile environments.
• Experience with machine learning model deployment in embedded environments.
• Experience with machine learning model deployment in real-time environments.
• Experience with machine learning model deployment in batch environments.
• Experience with machine learning model deployment in streaming environments.
• Experience with machine learning model deployment in event-driven environments.
• Experience with machine learning model deployment in serverless environments.
• Experience with machine learning model deployment in microservices environments.
• Experience with machine learning model deployment in monolithic environments.
• Experience with machine learning model deployment in service-oriented architectures.
• Experience with machine learning model deployment in microservices architectures.
• Experience with machine learning model deployment in event-driven architectures.
• Experience with machine learning model deployment in serverless architectures.

Compensation

Competitive salary and equity

Work Arrangement

Remote

Team

Collaborate with a team of experienced engineers and data scientists.

What You'll Do

• Develop and maintain machine learning models and pipelines.
• Collaborate with data scientists and engineers to integrate machine learning models into production systems.
• Ensure the performance, quality, and scalability of machine learning solutions.
• Monitor and optimize machine learning models and infrastructure.
• Implement and maintain data processing and storage solutions.
• Develop and maintain APIs and microservices for machine learning applications.
• Contribute to the development of machine learning frameworks and tools.
• Implement and maintain CI/CD pipelines for machine learning models.
• Conduct code reviews and pair programming sessions to ensure code quality.
• Troubleshoot and resolve issues in machine learning systems.
• Document machine learning models, pipelines, and systems.
• Stay up-to-date with the latest developments in machine learning and related technologies.
• Collaborate with cross-functional teams to define, design, and ship new features.
• Work on improving the scalability and performance of machine learning models.
• Develop and maintain machine learning infrastructure.
• Implement and maintain monitoring and logging solutions for machine learning systems.
• Contribute to the development of machine learning best practices and standards.
• Participate in on-call rotations to ensure the availability and reliability of machine learning systems.
• Conduct performance testing and optimization of machine learning models.
• Develop and maintain machine learning dashboards and visualizations.
• Collaborate with product managers to define and prioritize machine learning projects.
• Work on improving the accuracy and efficiency of machine learning models.
• Develop and maintain machine learning training and deployment pipelines.

What You'll Need

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Proven experience in software engineering, with a focus on machine learning.
• Strong programming skills in Python, Java, or a similar language.
• Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Experience with cloud platforms such as AWS, GCP, or Azure.
• Experience with containerization technologies such as Docker and Kubernetes.
• Experience with CI/CD pipelines and tools.
• Experience with data processing and storage solutions.
• Experience with APIs and microservices.
• Experience with monitoring and logging solutions.
• Experience with machine learning model deployment and management.
• Experience with machine learning model training and optimization.
• Experience with machine learning model evaluation and validation.
• Experience with machine learning model interpretation and explainability.
• Experience with machine learning model security and privacy.
• Experience with machine learning model governance and compliance.
• Experience with machine learning model versioning and management.
• Experience with machine learning model lifecycle management.
• Experience with machine learning model performance testing and optimization.
• Experience with machine learning model scalability and reliability.
• Experience with machine learning model monitoring and alerting.
• Experience with machine learning model debugging and troubleshooting.
• Experience with machine learning model documentation and communication.

Nice to Have

• Master's degree in Computer Science, Engineering, or a related field.
• Experience with machine learning model serving and inference.
• Experience with machine learning model training and deployment at scale.
• Experience with machine learning model A/B testing and experimentation.
• Experience with machine learning model deployment in production environments.
• Experience with machine learning model deployment in cloud environments.
• Experience with machine learning model deployment in on-premises environments.
• Experience with machine learning model deployment in hybrid environments.
• Experience with machine learning model deployment in multi-cloud environments.
• Experience with machine learning model deployment in edge environments.

Our Benefits

• Competitive salary and equity.
• Health, dental, and vision insurance.
• 401(k) matching.
• Unlimited PTO.
• Remote work options.
• Flexible work hours.
• Professional development opportunities.
• Employee assistance programs.
• Wellness programs.
• Employee resource groups.
• Diversity, equity, and inclusion initiatives.
• Community involvement opportunities.
• Employee recognition programs.
• Performance bonuses.
• Stock options.
• Relocation assistance.
• Tuition reimbursement.
• Parental leave.

Our Culture

• Collaborative and inclusive work environment.
• Focus on continuous learning and development.
• Emphasis on work-life balance.
• Encouragement of innovation and creativity.
• Commitment to diversity, equity, and inclusion.
• Support for professional growth and advancement.
• Opportunities for cross-functional collaboration.
• Flexible and remote work options.
• Emphasis on employee well-being and satisfaction.
• Focus on delivering high-quality products and services.

Our Mission

• To develop and deliver innovative machine learning solutions that drive business value.
• To empower our team members to achieve their full potential.
• To foster a culture of continuous learning and improvement.
• To build and maintain strong relationships with our customers and partners.
• To promote diversity, equity, and inclusion in all aspects of our work.
• To contribute to the advancement of machine learning and related technologies.
• To create a positive impact on society through our work.
• To deliver high-quality products and services that meet the needs of our customers.
• To innovate and stay ahead of the curve in the machine learning industry.
• To build a sustainable and successful business that benefits all stakeholders.

Our Values

• Integrity: We act with honesty, transparency, and accountability.
• Innovation: We embrace change and continuously seek new and better ways to do things.
• Collaboration: We work together to achieve common goals and support each other's success.
• Customer Focus: We prioritize the needs and satisfaction of our customers in all that we do.
• Excellence: We strive for the highest standards of quality and performance in our work.
• Respect: We value and respect the diversity of our team members and the communities we serve.
• Sustainability: We are committed to operating in a way that is environmentally, socially, and economically responsible.
• Continuous Learning: We encourage and support ongoing learning and development for all team members.
• Empowerment: We empower our team members to take ownership of their work and make decisions that drive success.
• Inclusivity: We foster a culture of inclusivity where everyone feels valued, respected, and heard.

How to Apply

• Submit your resume and cover letter through our online application system.
• Include a portfolio or samples of your work, if applicable.
• Highlight your relevant experience and skills in your application.
• Tailor your application to the specific requirements of the role.
• Follow up with the hiring team if you have any questions or need additional information.
• Prepare for a technical interview and assessment, if invited.
• Be ready to discuss your experience and qualifications in detail during the interview process.
• Provide references and any other relevant documentation, if requested.
• Follow the application instructions carefully and submit all required materials.
• Be patient and responsive throughout the application and interview process.

Equal Opportunity Employer

• We are an equal opportunity employer and welcome applicants from all backgrounds.
• We do not discriminate based on race, color, religion, sex, national origin, age, disability, or any other protected characteristic.
• We are committed to creating a diverse and inclusive work environment.
• We encourage applicants from underrepresented groups to apply.
• We provide reasonable accommodations to applicants with disabilities.
• We comply with all applicable laws and regulations related to equal employment opportunity.
• We promote a culture of respect, inclusion, and fairness in all aspects of our work.
• We value the unique perspectives and experiences that diversity brings to our team.
• We are dedicated to fostering a work environment where everyone can thrive and succeed.
• We believe that diversity and inclusion are essential to our success and the success of our customers.

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