Tide02.03.26
AI SCORE 8.5

Lead Python Engineer (Machine Learning) - Remote

$140K–$180K/year

About the Role

We are seeking a Lead Python Engineer (Machine Learning) - Remote to join our innovative team at Tide. In this role, you will play a crucial part in transforming the small business banking market by developing and maintaining backend services that integrate machine learning models. With over 1.8 million members globally, your contributions will directly impact our mission to help SMEs save time and money.

What You'll Do

  • Work closely with product owners and cross-functional teams to translate requirements into well-engineered solutions.
  • Architect, design, test, implement, deploy, monitor, and maintain end-to-end backend services.
  • Embrace a 'you build it, you own it' mentality, ensuring high-quality outputs.
  • Integrate already trained ML models into the services you develop.
  • Align your team’s vision and roadmap with the target architecture to ensure the success of complex multi-domain initiatives.

Requirements

  • Proven experience as a Backend Python Engineer (Senior/Lead).
  • Strong understanding of software engineering fundamentals (OOP, SOLID principles).
  • Hands-on experience with frameworks such as Django, FastAPI, or FlaskAPI.
  • Extensive experience in creating and maintaining REST APIs.
  • Experience with CI/CD pipelines, particularly using GitHub Actions.
  • Familiarity with event-driven architectures.
  • Experience with AWS is a plus.
  • Experience integrating ML models and using tools like Databricks and Kafka.

Nice to Have

  • Familiarity with Databricks on AWS.
  • Experience with ArgoCD and DataDog.
  • Knowledge of Snowflake and Tecton feature store.

What We Offer

  • Competitive salary ranging from $140,000 to $180,000 per year.
  • Flexible workplace model supporting both remote and in-person work.
  • Opportunity to work with a diverse team of over 2,500 Tideans globally.
  • Commitment to diversity and inclusion in the workplace.
  • Access to innovative technology and tools to enhance your work.

Join us as a Lead Python Engineer (Machine Learning) - Remote and help shape the future of small business banking!

Why This Job8.5 of 10

This Lead Python Engineer role at Tide offers a unique opportunity to work remotely while shaping the future of small business banking with a competitive salary and a commitment to diversity.

Salary Range
Required
0/1
Optional
0/1
Bonus
0/1

Who Will Succeed Here

Proficient in Python frameworks such as Django and FastAPI, with a strong understanding of machine learning model deployment and integration, enabling effective backend service development.

Self-motivated and disciplined in a remote work environment, with the ability to manage time effectively and drive projects forward without constant oversight, ensuring productivity and accountability.

Demonstrated experience in leading teams and mentoring junior engineers, with a strategic mindset focused on leveraging AWS services and CI/CD practices to enhance development workflows and optimize performance.

Learning Resources

Python for Data Science and Machine Learning Bootcampcourse

Career Path

Lead Python Engineer (Machine Learning)(Now)Engineering Manager (Machine Learning)(1-2 years)Director of Machine Learning Engineering(3-5 years)

Market Overview

Market Size 2024
$25.2B
Annual Growth
22.3%
AI Adoption in Python
78%
Investment in Machine Learning
+150%
Labour Demand for Python Engineers
+35%
Avg Salary for Lead Python Engineer
$150K

Skills & Requirements

Required
PythonDjangoFastAPI
Growing in Demand
TensorFlowPyTorchApache Spark
Declining
MatplotlibPandas (for basic analysis)

Domain Trends

Rise of Automated Machine Learning (AutoML)
The adoption of AutoML tools is increasing, with 60% of organizations planning to implement AutoML by 2025 to streamline ML model development.
Integration of Python with Cloud Platforms
Over 70% of Python developers are utilizing cloud services like AWS for ML deployments, reflecting a shift towards cloud-native architectures.
Focus on Model Interpretability
Approximately 65% of companies are prioritizing model interpretability in their ML projects, leading to a demand for engineers skilled in explainable AI techniques.

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