Senior Machine Learning Engineer - Payments
WFA Digital Insight
The demand for skilled machine learning engineers in the fintech industry has grown significantly, with a 25% increase in job postings over the past year. As a senior machine learning engineer at Plaid, you'll be at the forefront of this trend, working on cutting-edge projects that empower millions of users to manage their finances more effectively. With the company's commitment to innovation and customer satisfaction, this role is ideal for professionals looking to make a real impact. Candidates should be prepared to showcase their technical expertise, as well as their ability to collaborate and drive projects forward in a fast-paced environment.
Job Description
About the Role
The Senior Machine Learning Engineer role at Plaid is a unique opportunity to work on complex, high-impact machine learning challenges that improve the financial lives of millions of users. As a member of the core ML payments team, you'll be responsible for designing, building, and deploying scalable ML solutions and systems. Your work will have a direct impact on the company's mission to unlock financial freedom for everyone.The ideal candidate will have a strong background in machine learning and software engineering, with experience in building and deploying models in a production environment. You'll be working closely with a skilled team of engineers, data scientists, and product managers to develop and implement ML solutions that drive business impact.
Plaid's Machine Learning team is dedicated to building models that improve the way people interact with their finances. With a focus on innovation and customer satisfaction, the company is committed to creating a work environment that is collaborative, dynamic, and supportive.
What You Will Do
- Build and deploy scalable ML solutions and systems that drive business impact
- Design and implement machine learning models using state-of-the-art techniques, including natural language processing, anomaly detection, optimization, and time series forecasting
- Collaborate with cross-functional teams to develop and implement ML solutions that drive business impact
- Experiment with new modeling approaches and strategies to stay ahead of the curve
- Work on both 0-1 stage problems and 1-10 stage problems, driving projects forward from concept to deployment
- Develop AI/ML models in a full life cycle, from offline training to online serving and monitoring
- Dive deep into data and apply data-driven decisions in day-to-day work
- Take ownership of projects and drive them to completion, working independently and as part of a team
- Collaborate with teams across Plaid to define the ML roadmap and drive business impact
What We Are Looking For
- 5+ years of experience in training and serving AI/ML models in a production environment
- Experience in building and working with data-intensive backend applications in large distributed systems
- Ability to code and iterate independently on top of data infrastructure tools like Python, Spark, Jupyter notebooks, and standard ML libraries
- Strong understanding of machine learning concepts, including supervised and unsupervised learning, deep learning, and reinforcement learning
- Experience with cloud-based technologies, such as AWS or Google Cloud
- Strong communication and collaboration skills, with the ability to work with technical and non-technical teams
- Master's degree or equivalent work experience in Computer Science, Mathematics, Engineering, or a closely related field
- Experience with the industry application of NLP is a plus
- Experience with the FinTech industry is a plus
Nice to Have
- Experience with data analytics and data engineering
- Knowledge of containerization using Docker
- Experience with agile development methodologies
- Certification in machine learning or a related field
Benefits and Perks
- Competitive salary and equity package
- Comprehensive health, dental, and vision insurance
- Flexible PTO policy and remote work options
- Access to cutting-edge technologies and tools
- Opportunities for professional growth and development
- Collaborative and dynamic work environment
- Access to a network of talented professionals in the industry
- Annual budget for conference and training expenses
- Flexible spending accounts for health and wellness expenses
How to Stand Out
- Make sure to highlight your experience with machine learning technologies and frameworks, such as Python, TensorFlow, and scikit-learn.
- Showcase your ability to work with large datasets and build scalable ML solutions that drive business impact.
- Prepare to discuss your experience with cloud-based technologies, such as AWS or Google Cloud, and how you've used them to deploy ML models.
- Be ready to explain your approach to machine learning, including your understanding of supervised and unsupervised learning, deep learning, and reinforcement learning.
- Emphasize your strong communication and collaboration skills, and be prepared to provide examples of how you've worked with technical and non-technical teams in the past.
- Don't be afraid to ask about the company culture and values, and how they impact the way the team works and collaborates.
- Be prepared to discuss your long-term career goals and how this role fits into your overall career aspirations.
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