Senior ML Developer
Our client is transforming compliance through cutting-edge AI. Their platform automates anti-money laundering (AML) screening and investigations, enabling financial institutions and fintechs to streamline their workflows, reduce false positives, and focus on what truly matters—mitigating risk.
They are seeking a Senior ML Developer I to support AI and ML initiatives that include end-to-end deployment of ML models, data curation, ongoing model maintenance, feedback integration, model risk management, platform deployment, application integration, and ML infrastructure and pipeline development.
This position offers the opportunity to work on new and exciting projects, collaborate with cross-functional teams, and contribute to the overall success of the organization. It is ideal for a fast learner with a solid foundation in ML and CS who is looking to take on new challenges and responsibilities.
Collaborate with data scientists, product managers, and software engineers to design and deliver ML-powered features.
Own ML models end-to-end: development, deployment, integration with core systems, ongoing monitoring and maintenance.
Establish and champion best practices for ML development (unit testing, integration testing, model validation, CI/CD, monitoring drift, retraining, etc.), continuously improving quality and reducing technical debt.
Work with a modern technology stack: Python, PyTorch/TensorFlow, Databricks, Docker/Kubernetes, AWS, Datadog.
Write clean, efficient, and well-documented code.
Contribute to project planning: refine technical designs, break down tasks, estimate effort, ensure cross-functional alignment and timely delivery.
Stay up to date with advances in ML, frameworks, and infrastructure; evaluate new tools and approaches for adoption.
Take an active role in growing the team and partner with your manager to improve processes that support team development and efficiency.
Your work will directly power our client’s AI-driven risk intelligence platform, improving how customers make critical risk decisions.
5+ years as an ML developer, with hands-on experience deploying ML systems to production.
Strong MLOps expertise (must-have skills):
LLM deployment and optimization (fine-tuning, prompt engineering, serving at scale).
Model serving, maintenance, performance monitoring (data drift, model drift, bias detection, alerting).
System-level performance monitoring (latency, throughput, resource allocation).
Solid understanding of CI/CD pipelines for ML workloads.
Data ingestion, transformation, and monitoring pipelines.
Tools & Technologies
Proficiency in Python with strong software engineering practices (testing, version control, code quality).
Experience with SageMaker, Databricks, AWS, Kubernetes, Terraform.
Experience with C++ is a plus.
Additional Skills & Mindset
Strong ML / data science foundation (algorithms, evaluation, statistics).
Passion for working with cross-functional teams including Product and Business.
Startup mindset: enjoys tackling new challenges, adapts quickly to change, and operates effectively in a fast-moving environment.
A strong sense of ownership and pride in building high-quality systems.
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