Franklin Fitch
This range is provided by Franklin Fitch. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range
$220,000.00/yr - $320,000.00/yr Direct message the job poster from Franklin Fitch We’re looking for a
Director of Machine Learning Engineering
to lead the design, deployment, and scaling of ML systems that power the future of fintech. You’ll own the strategic direction of our ML roadmap, guide a high-performing engineering team, and partner with product and data leaders to drive innovation across the business. This is a rare opportunity to combine deep technical expertise with organizational leadership in a high-impact, early-stage environment. What You’ll Do
Define and own the
machine learning strategy , aligning it with product, risk, and business objectives Lead, mentor, and grow a team of ML engineers and data scientists, fostering a culture of technical excellence and experimentation Oversee the full ML lifecycle—from research and prototyping to production deployment, monitoring, and iteration Build and scale
ML infrastructure and platforms , enabling reproducibility, monitoring, and rapid experimentation Partner with executives, product managers, and business stakeholders to identify opportunities where ML provides competitive advantage Establish and enforce
best practices in MLOps, data governance, and responsible AI
(fairness, explainability, compliance) Drive continuous improvements in model performance, system reliability, and customer impact Represent ML engineering internally and externally, setting the technical vision for how we use AI to reshape fintech Who You Are
Proven leader with
7+ years in ML/AI engineering
and at least
3+ years in a leadership role Strong track record of building, scaling, and leading
ML engineering teams
in fast-paced environments Deep technical expertise in
ML modeling, distributed systems, and production-scale deployment Proficient in
Python, modern ML frameworks, and cloud platforms
(AWS/GCP/Azure) Experienced in
real-time decisioning systems , data pipelines, and large-scale APIs Strong understanding of
MLOps platforms
(MLflow, Kubeflow, Airflow, SageMaker, Vertex AI) and best practices Knowledge of
fintech-relevant domains : risk modeling, fraud detection, affordability, and predictive analytics Excellent communicator able to bridge
technical and business teams , influencing product direction and company strategy Entrepreneurial mindset: thrive in
high-ownership, early-stage environments , with the ability to scale both technology and teams Note: This refinement removes boilerplate and non-relevant postings while preserving the core responsibilities and qualifications for the role.
#J-18808-Ljbffr
$220,000.00/yr - $320,000.00/yr Direct message the job poster from Franklin Fitch We’re looking for a
Director of Machine Learning Engineering
to lead the design, deployment, and scaling of ML systems that power the future of fintech. You’ll own the strategic direction of our ML roadmap, guide a high-performing engineering team, and partner with product and data leaders to drive innovation across the business. This is a rare opportunity to combine deep technical expertise with organizational leadership in a high-impact, early-stage environment. What You’ll Do
Define and own the
machine learning strategy , aligning it with product, risk, and business objectives Lead, mentor, and grow a team of ML engineers and data scientists, fostering a culture of technical excellence and experimentation Oversee the full ML lifecycle—from research and prototyping to production deployment, monitoring, and iteration Build and scale
ML infrastructure and platforms , enabling reproducibility, monitoring, and rapid experimentation Partner with executives, product managers, and business stakeholders to identify opportunities where ML provides competitive advantage Establish and enforce
best practices in MLOps, data governance, and responsible AI
(fairness, explainability, compliance) Drive continuous improvements in model performance, system reliability, and customer impact Represent ML engineering internally and externally, setting the technical vision for how we use AI to reshape fintech Who You Are
Proven leader with
7+ years in ML/AI engineering
and at least
3+ years in a leadership role Strong track record of building, scaling, and leading
ML engineering teams
in fast-paced environments Deep technical expertise in
ML modeling, distributed systems, and production-scale deployment Proficient in
Python, modern ML frameworks, and cloud platforms
(AWS/GCP/Azure) Experienced in
real-time decisioning systems , data pipelines, and large-scale APIs Strong understanding of
MLOps platforms
(MLflow, Kubeflow, Airflow, SageMaker, Vertex AI) and best practices Knowledge of
fintech-relevant domains : risk modeling, fraud detection, affordability, and predictive analytics Excellent communicator able to bridge
technical and business teams , influencing product direction and company strategy Entrepreneurial mindset: thrive in
high-ownership, early-stage environments , with the ability to scale both technology and teams Note: This refinement removes boilerplate and non-relevant postings while preserving the core responsibilities and qualifications for the role.
#J-18808-Ljbffr