TCP is committed to cultivating a diverse and inclusive team. However, we are not able to sponsor visas for this role.
About TCP (TimeClock Plus):
For more than 30 years, TCP has helped organizations engage their people by providing flexible, mobile timekeeping and workforce management solutions. Trusted by tens of thousands of customers and millions of users, TCP delivers best-in-class technology and personalized support to organizations of all sizes in the public and private sector to meet their complex timekeeping, employee scheduling, leave management and other workforce needs. Growth is happening and our vision for a successful future is clear - We'd love for you to join us on this journey! For more information on TCP, visit www.tcpsoftware.com or follow us on LinkedIn or Facebook.
At TCP Software, we specialize in providing Time and Attendance and Employee Scheduling solutions that enhance productivity and streamline operations for businesses worldwide. We believe in the power of technology to simplify complex processes, and we’re looking for a talented Machine Learning Engineer to join our team and help drive our product innovation.
Position Overview:
We are seeking a passionate and skilled Machine Learning Engineer to work on developing and improving our AI-powered solutions. This position will involve training production models for a variety of machine learning tasks such as forecasting, anomaly detection, and event prediction, as well as leveraging cutting-edge libraries and technologies to build efficient and scalable systems.
Key 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 Product suite
- 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.
Required Qualifications:
- 5+ years of experience in training and deploying production models
- 5+ years of experience with the following libraries:
- 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)
Strongly Encouraged:
- 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:
Desired Skills & Attributes:
- Excellent problem-solving abilities and analytical thinking.
- Ability to work in a collaborative team environment while also being self-directed.
- Strong communication skills for explaining complex technical concepts to non-technical stakeholders.
- A passion for continuous learning and staying up-to-date with the latest advancements in machine learning and AI technologies.
Physical Requirements:
- Prolonged periods sitting at a desk and working on a computer.
- Must be able to lift up to 15 pounds at times.
Benefits:
- Competitive salary
- PTO and Sick leaves
- In-Patient Health insurance
- Provident fund and EOBI
- The work/life setup you need to be successful.
- A creative, collaborative, supportive environment that gives you the autonomy to explore new ideas, grow your skill set and create outstanding results
- The chance to make a genuine impact on the company’s growth
- Plenty of challenging work and the opportunity to stretch yourself
- The opportunity to work with amazing talent in a fast-growing company that really values their team
TCP is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.