Senior ML Solution Architect (Boston)
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Salary: $150,000 - $185,000 per year A bit about us: We are seeking a dynamic and experienced Senior Machine Learning (ML) Solution Architect to join our team. This is a unique opportunity to shape the future of our ML applications and contribute to the development of our technology stack. The successful candidate will be responsible for designing, implementing, and maintaining ML solutions that will have a direct impact on our business and customers. This is a permanent position that offers a challenging and rewarding work environment, where innovation and initiative are highly valued. Why join us?
- Competitive Base Salary
- Company paid health plan for employees
- Flexible Hours
- Very generous PTO
- Dental and Vision, FSA, HSA
- Small team, autonomy
- Many more great perks!
- Design and build robust and scalable ML solutions to meet business requirements.
- Work closely with data scientists and engineers to implement and deploy scalable ML solutions into production.
- Develop and maintain data pipelines for large scale data processing.
- Use tools such as Spark, Snowflake, Python, and Scala to handle data extraction, cleaning, and transformation.
- Implement best practices for ML development, including testing, documentation, and version control.
- Collaborate with cross-functional teams to understand their needs and translate them into ML solutions.
- Provide consulting services to internal and external stakeholders on ML best practices and solutions.
- Use Terraform, Docker, and other tools to manage infrastructure and deploy ML models.
- Implement and manage CI/CD pipelines for ML solutions.
- Stay up-to-date with the latest developments in the field of ML and introduce new technologies and methodologies as appropriate.
- Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field.
- Minimum 5 years of experience in designing and implementing ML solutions.
- Strong programming skills in Python and Scala.
- Experience with data pipeline tools such as Spark and Snowflake.
- Proven experience in consulting, with excellent communication and problem-solving skills.
- Experience with infrastructure management tools such as Terraform and Docker.
- Experience in setting up and managing CI/CD pipelines.
- Strong understanding of ML algorithms and principles, as well as the ability to apply them in real-world situations.
- Excellent analytical and problem-solving skills, with the ability to handle complex data and ML challenges.
- Strong communication skills, with the ability to explain complex concepts to non-technical stakeholders.
- Self-motivated and proactive, with the ability to work independently and as part of a team.
- Strong desire to learn and stay updated with the latest advancements in the field of ML.
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