Senior ML Engineer

We owe our success to the strength of our team. Before joining Main Street, we helped build companies like Intuit, Pay Pal, Google, Apple, Coinbase, Gusto, Linked In, Slack, and more. We’re fellow founders, engineers, accountants, designers, dog (and cat) lovers, adventurers, coders, and parents. We move fast. We think big. We don’t take ourselves too seriously. And we’d love for you to join us.

The opportunity

Main Street is looking for a Machine Learning Engineer who will play a pivotal role in designing, developing, and implementing machine learning models and algorithms that power our groundbreaking product. You will work closely with a team of talented engineers and data scientists to create intelligent systems that solve complex problems and unlock new possibilities that lead to dollars earned for our customers.

What you’ll do

• Research and Development:
  Conduct research to explore state-of-the-art machine learning algorithms, stay updated on the latest advancements, and propose innovative solutions to tackle business challenges effectively
• Model Development:
  Design, build, and optimize machine learning models and algorithms that can be deployed on various platforms and integrated into our products
• Data Preprocessing:
  Prepare and clean datasets to ensure they are suitable for model training and validation, while addressing issues such as missing data and outliers
• Model Training and Evaluation:
  Train machine learning models using vast datasets, validate their performance, and fine-tune hyperparameters to achieve optimal accuracy and generalization
• Integration and Deployment:
  Collaborate with software engineering teams to integrate machine learning models into production systems and ensure seamless deployment in real-world environments
• Performance Monitoring:
  Implement monitoring and logging mechanisms to track model performance in production and detect potential anomalies or degradation in accuracy
• Continual Improvement:
  Conduct thorough analysis of model performance, identify areas for improvement, and iterate on existing models to enhance their effectiveness
• Collaboration:
  
  Collaborate with cross-functional teams, including data scientists, software engineers, product managers, and stakeholders, to define project requirements and ensure alignment with business objectives
• Documentation:
  Create clear and comprehensive documentation for models, algorithms, and implementation processes, enabling easy knowledge transfer within the team
• Innovation and Research Contribution:
  Stay up-to-date with the latest trends and advancements in machine learning, participate in research discussions, and contribute to the company's intellectual property through patent filings and publications

What we’re looking for

• Education:
  
  Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field. A Ph.D. is a plus
• Experience:
  
  Demonstrable experience in developing and deploying machine learning models in real-world applications. (7 years of experience, depending on the seniority level)
• Programming
  
  Skills:
  
  Proficiency in programming languages like Python, R, or similar, along with experience in using machine learning libraries such as Tensor Flow, PyTorch, or scikit-learn
• Mathematics and Statistics:
  Strong understanding of linear algebra, calculus, probability, and statistics, coupled with the ability to apply these principles to machine learning problems
• Deep Learning:
  Familiarity with deep learning techniques, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformer models
• Data Handling:
  Experience with data preprocessing, feature engineering, and data augmentation techniques to enhance model performance
• Software Engineering:
  Understanding of software engineering principles, version control, and the ability to write clean, modular, and maintainable code
• Problem-Solving:
  Analytical mindset with a proven ability to break down complex problems, develop innovative solutions, and troubleshoot issues effectively
• Communication:
  Strong verbal and written communication skills, with the ability to convey complex technical concepts to both technical and non-technical…