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.
Role Overview
We seek an innovative and forward-thinking ML Ops Engineer specializing in Model Development. This role is designed for someone who thrives on the intersection of technical excellence and strategic insight and is capable of navigating the complexities of machine learning models while coordinating the Model Deployment with data scientists. You will be part of a dynamic team tasked with designing and implementing scalable, efficient, and reliable model training and evaluation processes.
Responsibilities
· Collaborate closely with clients to deeply understand their business challenges, translating these into actionable business problems that machine learning models can solve.
· Focus on Model Development and Deployment coordination with data scientists for designing and implementing scalable, efficient, and reliable model training and evaluation processes.
· Implement CI/CD pipelines for machine learning models using tools like AWS.
· Code Pipeline /AWS Cloud formation / Terraform. Enabling seamless deployment and integration into production systems.
· Automate the build, testing, and deployment processes to ensure smooth and efficient delivery of updated models.
· Implement monitoring solutions to track the performance and behavior of deployed models in real-time.
· Set up alerts and notifications to proactively identify issues, such as model degradation or data drift, and take appropriate actions.
· Optimize the performance and cost efficiency of machine learning workflows on AWS Sage maker.
· Fine-tune the infrastructure settings, explore autoscaling capabilities, and utilize spot instances for cost-effective model training and inference.
· Work alongside cross-functional teams to identify, assess, and mitigate risks associated with model performance and compliance, ensuring alignment with business objectives and regulatory requirements.
· Develop processes for continuous monitoring and performance testing of models, identifying opportunities for improvement and innovation within the ML Ops ecosystem.
Qualifications
· Bachelor’s / Master’s degree in Engineering, Economics/Statistics, or equivalent field.
· Minimum of 4+ years of relevant ML Ops experience in building robust machine learning pipelines in production.
· Industry domain experience within insurance, healthcare, financial services, or a related area is strongly preferred.
· Hands-on experience in deploying and managing containerized applications using Kubernetes and Docker for scalable and resilient infrastructure in ML Ops environments.
· Understanding of ML gateway and load balancing.
· Understanding of machine learning lifecycle, model building process, ability to build model implementation pipelines, model evaluation, drift detection, etc.
· Experience with Kafka for efficient data streaming and real-time data processing in distributed systems.
· Data monitoring tools such as Datadog or similar technology
· Knowledge of working with Vertex AI
· Experience in setting up and managing Continuous Integration and Continuous Deployment (CI/CD) pipelines, automating testing, deployment, and monitoring processes in MLOps and DevOps workflows.
· Git, Control M, ETL experience,
· Proficiency in programming languages such as Python, R, or Scala, essential for scripting and automation in MLOps workflows.
· Understanding of NLP Models.
Other Requirements
· Ability to be present at the client office for at least 3 days a week.
· Openness to travel up to 25% of the time to meet business needs.
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: $110,000 - $160,000. 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 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.