Fractal Analytics

Senior MLOPS Engineer

New York, NY US
USD 182k - 182k
API Azure AWS Docker Git Shell Python GCP Machine Learning Kubernetes
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Description

It's fun to work in a company where people truly BELIEVE in what they are doing!

We're committed to bringing passion and customer focus to the business.

Fractal Analytics is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite empowers imagination with intelligence. And that it will be such Fractalites that will continue to build the company for the next 100 years.

Please visit Fractal | Intelligence for Imagination for more information about Fractal.

Do you thrive at building and automating the infrastructure for machine learning models? Are you passionate about bridging the gap between data science and production? If so, we want to hear from you!

Role Overview:

We are seeking a highly skilled ML Ops Engineer to join our team and play a critical role in the development and deployment of our machine learning models. You will be responsible for the entire ML lifecycle, from data pipelines to production monitoring.

Responsibilities:

  • Design, develop, and implement CI/CD pipelines for machine learning models using tools like Airflow or similar solutions.

  • Leverage AWS services like S3, Cloudwatch, Lambda, EventBridge, and SageMaker to build, deploy, and monitor machine learning models in production.

  • Integrate models with other AWS functionalities for logging, observability, scaling, etc.

  • Containerize models using Docker and orchestrate deployments using Kubernetes.

  • Collaborate with data scientists to understand model requirements and translate them into production-ready solutions.

  • Implement best practices for version control (Git) and maintain comprehensive documentation for all ML pipelines.

  • Continuously monitor model performance and identify opportunities for improvement.

  • Troubleshoot and debug issues related to ML pipelines and infrastructure.

  • Stay up-to-date on the latest advancements in MLOps and related technologies.

Qualifications:

  • 5+ years of experience in a related field, such as Machine Learning Engineering, Data Engineering, or Software Engineering.

  • Strong experience in the AWS ecosystem, including S3, Cloudwatch, Lambda, EventBridge, Git integration, ECR, etc.

  • Proven experience building and deploying machine learning pipelines in AWS SageMaker.

  • Expertise in tools like Docker, Kubernetes, Airflow, Snowflake, and DBT.

  • Experienced in building webhooks that integrate with pipelines to generate alerts/APIs

  • Solid understanding of Linux and shell scripting.

  • Expertise in Python programming.

  • Experienced in building cross-platform orchestration frameworks and workflows that are optimized for scale and time.

  • Experience with Snowflake and Snowpark APIs for ETL operations

  • Strong focus on building solutions that adhere to security and compliance procedures

  • Excellent communication and collaboration skills.

  • Proactive and results-oriented with a strong work ethic.

Bonus Points:

  • Experience with model explainability and fairness tools.

  • Experience with other cloud platforms such as GCP, Azure

We offer a competitive compensation package and a chance to work on cutting-edge machine learning projects. If you are a passionate and talented ML Ops Engineer who is looking to make a real impact, we encourage you to apply!

Pay:

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs.  The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled.  At Fractal, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case.  A reasonable estimate of the current range is: $82,000 - $182,000 USD. In addition, for the current performance period, you may be eligible for a discretionary bonus.

Benefits:

As a full-time employee of the company or as an hourly employee working more than 30 hours per week, you will be eligible to participate in the health, dental, vision, life insurance, and disability plans in accordance with the plan documents, which may be amended from time to time.  You will be eligible for benefits on the first day of employment with the Company.  In addition, you are eligible to participate in the Company 401(k) Plan after 30 days of employment, in accordance with the applicable plan terms.   The Company provides for 11 paid holidays and 12 weeks of Parental Leave. We also follow a “free time” PTO policy, allowing you the flexibility to take the time needed for either sick time or vacation.

Fractal provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. 

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!

Not the right fit?  Let us know you're interested in a future opportunity by clicking Introduce Yourself in the top-right corner of the page or create an account to set up email alerts as new job postings become available that meet your interest!

Fractal Analytics
Fractal Analytics
Analytics Artificial Intelligence (AI) Big Data Business Intelligence Consulting InsurTech Machine Learning

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