Reejig is the leading global workforce intelligence platform that helps organizations find, mobilize, upskill, and optimize their workforce. Our mission is Zero Wasted Potential, and we are dedicated to ensuring everyone has access to meaningful careers. As a World Economic Forum Technology Pioneer, 2023 HR Tech Product of the Year, and Forbes Cloud 100 Rising Star, we are shaping the future of work with AI-driven solutions.
How we work
At Reejig, we envision a future of work that breaks from traditional paradigms. We are pioneers, in cultivating a workforce that is not merely a collection of full-time employees, but an optimized blend of fixed and flex workers, including the remarkable capabilities of generative AI. We call this our ‘Workforce DNA’—a harmonious integration of diverse work styles that fosters innovation, adaptability, and growth.
Our team members are provided the opportunity to engage in the most meaningful work, allowing their unique skills to shine while contributing to our shared goals. This hybrid model of workforce strategy liberates our employees from conventional roles, promoting a dynamic work environment that thrives on collaboration, intellectual diversity, and technological advancement. Join us at Reejig, as we lead the charge into a new era of work, shaping an inclusive and resilient workforce of tomorrow.
Reejig is seeking an experienced Senior Machine Learning Engineer to join our remote team based in Sydney. This is a fantastic opportunity to be part of a venture-backed, rapidly scaling startup where you'll use cutting-edge technologies to solve fascinating problems and make a significant impact.
Responsibilities:
Algorithm and Model Development: Develop and refine algorithms and models leveraging deep knowledge of data schema, quality, rationale, and domain expertise.
Data Selection and Feature Engineering: Identify and select relevant data points, and perform feature engineering to optimise model performance.
Model Setup and Tuning: Choose and set up appropriate algorithms, fine-tune parameters, and continuously evaluate and monitor their performance.
End-to-End ML Pipeline: Design, implement, and maintain end-to-end production level machine learning pipelines on AWS, ensuring seamless integration and deployment.
ML Models and LLMs: Utilise machine learning models and large language models (LLMs) to meet business needs, and develop effective prompts to enhance LLM interactions and outputs.
Data Operations: Conduct bulk and incremental data operations to ensure data integrity and accessibility.
Collaboration: Partner with cross-functional teams, including data scientists, engineers, and domain experts, to drive successful project outcomes.
Continuous Learning: Stay updated with the latest advancements in machine learning and related fields to continuously improve skills and apply new techniques.
The ideal candidate will have:
Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field.
Minimum 5+ years of proven experience as an ML Engineer or similar role (e.g. Data Scientist or Data Engineer), with a focus on algorithm development and model building.
Must have extensive hands-on experience in NLP techniques and tools (language modeling, text classification, named entity recognition) with a proven track record of applying these in real-world projects.
High proficiency in Python, and experience with ML frameworks like Keras, TensorFlow, PyTorch, or Scikit-learn.
Strong understanding of data schema, data quality, and data rationale, with the ability to work with large datasets and perform feature engineering.
Experience in setting up and maintaining end-to-end machine learning pipelines, including model selection, training, tuning, and deployment.
Proficient in utilising AWS cloud services for developing, deploying, and maintaining machine learning models and pipelines.
Familiarity with large language models (LLMs) and prompt engineering techniques.
Experience in performing bulk and incremental data operations.
Strong analytical and problem-solving skills, with a detail-oriented mindset.
Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams and a fast paced environment.
A proactive approach to learning and applying new techniques to improve machine learning models and processes.
Why Join Reejig:
At Reejig, we're committed to creating a diverse and inclusive workplace. We welcome applicants of all backgrounds and identities. Reach out and apply now!
