Software Engineer II - Machine Learning

Summary

Join TCP, a leading provider of timekeeping and workforce management solutions, as a Machine Learning Engineer. You will play a key role in developing and improving our AI-powered solutions by training and deploying production-level machine learning models for forecasting, anomaly detection, and event prediction. This position requires experience with Pytorch, Pandas, and Numpy, as well as a solid understanding of various model architectures. You will collaborate with cross-functional teams and work with large datasets to build efficient and scalable systems. TCP offers a full remote work option, a personalized benefits plan, and a competitive salary. We are committed to creating an inclusive environment for all employees.

Requirements

• 2+ years of experience in training and deploying production models
• 2+ years of experience with the following libraries: Pytorch
• Pandas
• Numpy
• Hands-on experience with language models
• Solid understanding of the following model architectures: Transformers
• RNN (Recurrent Neural Networks)
• S4 | Mamba
• LSTM (Long Short-Term Memory Networks)

Responsibilities

• Train and deploy production-level machine learning models focused on: Forecasting
• Anomaly Detection
• Event Prediction
• Develop and implement machine learning algorithms, ensuring their scalability, performance, and robustness
• Create agentic language model based user experiences
• Work with large datasets, process and analyze data using tools like Pandas and Numpy
• Use modern deep learning frameworks such as Pytorch to implement and optimize models
• Integrate machine learning models into the company’s Time and Attendance and Employee Scheduling software
• Collaborate with cross-functional teams to solve complex business challenges through AI/ML solutions
• Optimize and fine-tune models for performance in real-world production environments

Preferred Qualifications

• Familiarity with advanced machine learning concepts, including: State Space Modeling (S4, Mamba)
• Hidden Markov Models (HMMs)
• BEAM Search
• Human Feedback Reinforcement Learning (RLHF)
• Relationship Graph Theory
• Automatic Prompt Optimization
• Worked on language model user experiences using: DSPy
• LangChain

Benefits

• Full remote work, with the option to work from the office, based on personal preference
• Personalised and individual benefits plan
• Competitive salary based on experience
• Voluntary Health insurance plan
• International working environment
• 8 hours to volunteer and impact the community
• The work/life setup you need to be successful
• The opportunity to work with amazing talent in a fast-growing company that really values their team