Machine Learning Engineering Manager - Finance Industry

At Truelogic we are a leading provider of nearshore staff augmentation services headquartered in New York. For over two decades, we’ve been delivering top-tier technology solutions to companies of all sizes, from innovative startups to industry leaders, helping them achieve their digital transformation goals.

Our team of 600+ highly skilled tech professionals, based in Latin America, drives digital disruption by partnering with U.S. companies on their most impactful projects. Whether collaborating with Fortune 500 giants or scaling startups, we deliver results that make a difference.

By applying for this position, you’re taking the first step in joining a dynamic team that values your expertise and aspirations. We aim to align your skills with opportunities that foster exceptional career growth and success while contributing to transformative projects that shape the future.

A mission-first financial service provider dedicated to helping under-served customers in emerging markets to achieve financial stability and success. Lending through a patented technology that turns a smartphone into digital collateral and cutting-edge machine learning, data science, and anti-fraud AI allow them to offer the lowest cost and qualify the most customers in the industry. As of 2024, we have brought billions of dollars in credit to 12 million customers, doubling in the last two years while remaining strongly profitable and sustainable for the long term.

The Machine Learning Engineering Manager is responsible for the whole lifecycle of our ML modeling function from the feature generation to the model rollout (design, development, deployment, and monitoring), leading a talented team of machine learning engineers to develop, optimize, and deploy ML models that power our fraud detection, credit risk and other applications like cross-sell, churn and collections; continuously improving the quality and performance of our models by gathering and integrating new data sources that enhance our predictive capabilities.

Responsibilities

• Lead and manage a team of machine learning engineers to deliver high-quality and scalable ML models.

• Provide mentorship, guidance and career development to the ML engineers in the team, fostering a culture of collaboration and innovation by encouraging experimentation and adopting best practices and new technologies in DS/ML.

• Drive the development of new machine learning models to be delivered on each of our markets and ensure they are production-ready, optimized for scale and continuously improved based on feedback from our stakeholders and performance on production.

• Collaborate with global teams including Risk, Fraud, Engineering and Product to deliver world-class data science products to international markets.

• Lead the testing, cost-benefit analysis and integration of new data sources to improve the accuracy and robustness of our ML models.

• Work closely with our ML Platform and Tooling team to design and implement scalable feature generation and extraction pipelines and model deployment/monitoring processes.

Qualifications and Job Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field

• 5+ years of experience as a data scientist, machine learning engineer, data engineer or a closely related position with a proven track record of writing production-level code and developing and maintaining ML models in production.

• Strong leadership and people management skills with at least 2 years of experience leading and scaling high-performing teams.

• High proficiency in Python and a strong understanding of its related libraries and frameworks (e.g., Scikit-Learn, Pandas, Flask, etc).

• Comprehensive knowledge of ML life cycle: from data extraction and feature engineering to model serving and monitoring for live and batch processing.

• Demonstrated experience with cloud providers (AWS preferred) and related services like containerization (e.g., Docker).

• Experience in credit risk modeling, fraud detection or other applications of machine learning in the financial market is a big plus.

• Good verbal and written communication skills in English.

What We Offer

• 100% Company-funded Health and Dental insurance for employees and immediate family members.

• Life insurance.

• Phone finance, headphones, home office equipment, and fitness perks.

• 30 days of Christmas bonus

• 20 days paid Vacation

• 50% Vacation premium

• 13% Saving funds

• $2,000 MXN monthly grocery coupons

• $2,000 USD annual Co-working Travel perk

• $2,000 USD annual Professional Development perk

Extra Info

It's required to go to the office in Col. Cuauhtémoc (CDMX), 3 times per week.

Apply now!