Lead MLOps Engineer

At Clicklease, we're on a unique mission – to empower the small business owners often overlooked by traditional lenders. If you're considering joining our team, envision yourself at the heart of our vibrant headquarters in West Valley City, UT, or contributing to our impactful operations from Radial, Alajuela, Costa Rica. At Clicklease, we've cultivated a dynamic work environment that goes beyond routine services. At Clicklease, you'll play a pivotal role in transforming equipment financing into a gateway for entrepreneurs to turn their dreams into reality. If you're passionate about purpose-driven work, innovation, and making a tangible impact, Clicklease is where your career journey begins.

Join us in shaping a future where every business owner has the opportunity to thrive.

Are you an experienced Lead MLOps Engineer? Clicklease invites you to lead our machine learning operations within the Risk Department. Apply now to spearhead the robustness, scalability, and continuous improvement of our ML systems. We're seeking individuals with a strong background in machine learning, data engineering, and cloud infrastructure, ready to strategically implement and operationalize ML models. Join us and make a difference!

Compensation: $160,000 - $200,000 based on experience
Modality: Hybrid (3 days in office, 2 days remote)
FLSA Exemption: Exempt
Schedule: Monday to Friday, 9:00 AM - 5:00 PM

What you’ll be doing:

• Develop, deploy, and manage machine learning workflows using MLOps tools such as Kubeflow, Dagster, and MLFlow, focusing on automation and reproducibility.

• Design and construct Directed Acyclic Graphs (DAGs) for workflow orchestration with Apache Airflow, ensuring efficient and reliable execution of complex data pipelines.

• Leverage AWS cloud services to build and scale machine learning solutions, ensuring high availability and performance.

• Integrate and manage data analytics platforms such as Snowflake, optimizing data workflows for ML model training and inference.

• Provide expertise in end-to-end machine learning lifecycle management from data preparation to model deployment, monitoring, and maintenance.

• Mentor and train data science teams on best practices in MLOps, promoting a culture of excellence and continuous learning.

• Stay ahead of the curve in machine learning operations, applying industry best practices and exploring emerging technologies to enhance our MLOps capabilities.

What you have:

• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical field.

• 5+ years of experience in machine learning, data engineering, or a related role, with a focus on MLOps.

• Demonstrated proficiency in MLOps platforms (Kubeflow, MLFlow), workflow orchestration (Airflow), and cloud services (AWS).

• Strong experience with SQL and data warehousing solutions like Snowflake.

• Deep understanding of the ML model development lifecycle, including data preparation, model training, versioning, deployment, and monitoring.

• Strong analytical and problem-solving skills, capable of working in a dynamic environment.

• Excellent communication skills, adept at engaging with both technical and non-technical stakeholders.

What will make you stand out:

• Master's or PhD in a related technical discipline.

• Certifications in AWS, Snowflake, or other relevant technologies.

• Proven track record of successful MLOps system implementations in a finance or risk management context.

• Contributions to open-source MLOps projects or thought leadership in the MLOps community.