Associate Machine Learning Engineer

Job Description

Managing pricing and rebates shouldn’t be a hassle. Enable’s intelligent platform is built for the speed of today’s market, eliminating disconnects between pricing strategy and rebate execution. We help companies to increase profitability and simplify the complex with accurate, AI-powered insights, real-time performance monitoring, agreement optimization, and simplified rebate management.

After securing $291M in Series A-D funding and acquiring Flintfox in 2025, Enable is positioned for continued, significant growth. Since the launch of our flagship product in 2016, we have been rapidly scaling our client base, product offerings, and built a team of top-tier professionals committed to reshaping the industry.

Want a glimpse into life at Enable? Visit our Life at Enable page to learn how you can be part of our journey.

Job Summary

We are seeking a detail-oriented engineer passionate about the foundational elements of machine learning. This individual will play a key role in building robust data pipelines, improving dataset quality, and streamlining model deployment processes. The ideal candidate is a junior engineer eager to learn how clean data and seamless operations power impactful ML solutions across the business.

Duties & Responsibilities

Support data quality assurance by cleaning, validating, and auditing datasets to ensure accuracy and completeness.

Identify and resolve data anomalies, biases, and missing values in partnership with data engineering teams.

Assist in the development of automated validation tools using Python (pandas, Great Expectations).

Contribute to synthetic data creation efforts by helping design synthetic datasets to augment training data or simulate edge cases.

Learn techniques such as GANs, VAEs, and rule-based simulation under mentorship.

Test and evaluate synthetic data efficacy in model training pipelines.

Assist with automated labeling by supporting labeling pipelines using tools such as Snorkel, weak supervision, or active learning.

Collaborate with annotation teams to improve labeling workflows and reduce manual intervention.

Provide MLOps support in deploying and monitoring models in production environments (Azure) using tools such as Docker, Airflow, or MLflow.

Assist in building CI/CD pipelines for automated model testing and retraining.

Help document processes and maintain performance dashboards.

Knowledge, Skills & Abilities (KSAs)

Foundational knowledge of Python (NumPy, pandas) and basic SQL.

Familiarity with data preprocessing and validation techniques, with an interest in synthetic data tools such as Synthea or Faker.

Curiosity and developing skills in MLOps tools such as Kubeflow or TFX and cloud environments (AWS, GCP, Azure).

Strong analytical and problem-solving abilities with attention to data integrity and systematic execution.

Effective communication skills for cross-functional collaboration across technical and non-technical teams.

Required Education & Experience

Bachelor’s degree in Computer Science, Data Science, or a related technical field, or equivalent practical experience.

Foundational experience working with data pipelines, model development, or ML workflows through coursework or early professional projects.

Preferred Education & Experience

Hands-on experience or academic projects involving data engineering, synthetic data generation, or automated labeling.

Familiarity with labeling platforms such as Label Studio or Scale AI and workflow orchestration tools such as Airflow.

Basic knowledge of statistical methods for data quality and bias analysis.

Total Rewards:

At Enable, we’re committed to your professional development and growth. Starting pay is determined by factors like location, skills, experience, market conditions, and internal parity.

Salary/TCC is just one component of Enable’s total rewards package. Enable is committed to investing in the holistic health and wellbeing of all Enablees and their families. Our benefits and perks include, but are not limited to:

Paid Time Off: Take the time you need to relax and recharge

Wellness Benefit: Quarterly incentive dedicated to improving your health and well-being

Comprehensive Insurance: Health and life coverage for you and your family

Retirement Plan: Build your future with our retirement savings plan

Lucrative Bonus Plan: Enjoy a rewarding bonus structure subject to company or individual performance

Equity Program: Benefit from our equity program with additional options tied to tenure and performance

Career Growth: Explore new opportunities with our internal mobility program

Additional Perks:  

Free Food: Complimentary meals, snacks, and drinks on-site in our global offices  

Training: Access a range of workshops and courses designed to boost your professional growth and take your career to new heights 

Pets: Bring your pets to our welcoming, pet-friendly offices

According to LinkedIn's Gender Insights Report, women apply for 20% fewer jobs than men, despite similar job search behaviors. At Enable, we’re committed to closing this gap by encouraging women and underrepresented groups to apply, even if they don’t meet all qualifications.

Enable is an equal opportunity employer, fostering an inclusive, accessible workplace that values diversity. We provide fair, discrimination-free employment, ensuring a harassment-free environment with equitable treatment.

We welcome applications from all backgrounds. If you need reasonable adjustments during recruitment or in the role, please let us know.

Please mention that you found this job on MoAIJobs, this helps us grow. Thank you!