The Lead ML/AI Platform Engineer position at SavvyMoney is a full-time remote role based in Europe that suits an experienced machine learning professional looking to own production AI infrastructure. This independent contractor opportunity involves building the foundational machine learning and generative AI platforms that power digital banking solutions for millions of consumers.
Role Overview
As a Lead ML/AI Platform Engineer at SavvyMoney, the person in this role will own the platform that takes machine learning from experiment to production. Responsibilities include training infrastructure, model serving, inference pipelines, and integration seams with Java microservices. This position establishes technical direction for artificial intelligence and machine learning alongside the Data Platform Architect, driving the engineering side of generative AI, large language models, and agent strategies.
Key Responsibilities
Partner with the Data Platform Architect to set technical direction for AI and machine learning across the organization.
Own the end-to-end ML/AI platform, covering training infrastructure, model serving, inference pipelines, and production integration.
Execute feature engineering, model training, model registry, and hosted inference using Amazon SageMaker.
Drive generative AI and large language model usage, fine-tuning, and agentic workflows within Amazon Bedrock and AgentCore.
Manage feedback and data pipelines utilizing AWS Glue, Lambda, and Step Functions.
Own the serving layer, integrating machine learning services cleanly with Java microservices by defining API contracts and evaluating latency and throughput trade-offs.
Guide the engineering side of the generative AI strategy, including retrieval architectures and evaluation harnesses.
Implement guardrails required to run agentic workflows responsibly within a regulated environment.
Partner with data scientists on the handoff from experimentation to production by standing up necessary feature pipelines and serving infrastructure.
Collaborate with product, data, and engineering leadership to identify high-impact machine learning opportunities.
Requirements
Minimum of 8 years of experience in software or machine learning engineering.
At least 5 years of experience shipping production machine learning systems with a track record of solving ambiguous, high-scope problems end to end.
Demonstrated technical leadership in shaping machine learning strategy and mentoring senior engineers.
Hands-on experience with the AWS managed machine learning stack, including Amazon SageMaker, Amazon Bedrock, and AgentCore.
Familiarity with open-source machine learning tooling such as JupyterLab, Spark, and MLflow.
Deep working knowledge of the AWS ecosystem including S3, Athena, Redshift, Glue, Step Functions, and Lambda, alongside strong SQL skills.
Production experience with generative AI and large language models covering retrieval-augmented generation, prompt engineering, and evaluation.
Familiarity with vector databases like pgvector and Pinecone.
Working knowledge of Java to review service code and debug integration issues with microservices.
Deep expertise in Python and core machine learning libraries including scikit-learn, pandas, NumPy, PyTorch, TensorFlow, and XGBoost.
Solid MLOps fundamentals covering model monitoring, drift detection, reproducibility, and experiment tracking.
Excellent written and verbal communication skills with the ability to operate as an independent contractor with overlap for US Pacific business hours.
Nice to Have
Experience with ClickHouse or comparable columnar and real-time analytical databases.
Fine-tuning experience including LoRA, QLoRA, instruction tuning, or reinforcement learning from human feedback.
Streaming and real-time inference experience using Kafka, Kinesis, or low-latency serving.
Infrastructure-as-code experience with Terraform, AWS CDK, or CloudFormation.
Experience operating machine learning systems at scale processing hundreds of millions of predictions daily.
Open-source contributions, conference talks, papers, or patents in applied machine learning.
Skills and Tools
Python
PyTorch
TensorFlow
SQL
AWS
Java
Spark
LLMs
RAG
MLOps
Kafka
Terraform
Salary and Benefits
Equity Compensation Package
Flexible Time Off (FTO)
Medical, Dental, and Vision insurance with 100 percent premium paid for employees
Disability and Life Insurance
Learning and career growth opportunities
Reimbursement for remote work setup
Monthly stipend for phone and internet
Team building events, culture activities, and all-hands events
Paid time off to volunteer and serve the community
Half day Fridays
401k matching contribution
About the Company
SavvyMoney is a leading United States-based financial technology company providing integrated credit score and personal finance solutions to over 1,600 bank and credit union partners. Solutions integrate with more than 43 digital banking platforms. Recognized as a top workplace and a fast-growing company, SavvyMoney values diversity of culture and thought to deliver practical solutions.
How to Apply
Interested candidates should visit the official SavvyMoney careers page to submit an application for this remote opportunity.
