PLEASE NOTE THIS IS AN EQUITY-ONLY ROLE AND THE INTERVIEWS WILL COMMENCE IN FEBRUARY 2025.

Stealth-Mode Start-Up Client is seeking askilled Machine Learning Engineerto design, build, and deployAI/ML modelsthat powerpersonalized recommendations, predictive analytics, andreal-time data insightson a global platform. This role will focus ondeveloping machine learning pipelines, fine-tuning algorithms, and ensuring scalable deployment of AI-driven features across bothweb and mobile environments.

The ideal candidate will have a strong background inmachine learning, data science, andsoftware engineering, with experience in building and deployingscalable AI systems.

To apply, please provide a CV, your compensation requirements (including salary expectations for when funding is secured) and a cover letter/note that explains why you are interested and how you meet the requirements. Please note that submissions received without all the requested information will be automatically disqualified and rejected.

Key Responsibilities:

• Design, build, and deploymachine learning modelsfor tasks such as user behaviour prediction, content recommendations, and fraud detection.
• Develop and maintainend-to-end machine learning pipelinesfrom data collection and preprocessing to model deployment and monitoring.
• Collaborate withData EngineersandProduct Teamsto seamlessly integrate AI capabilities into product workflows.
• Build real-time ML systems capable of handlingdynamic data streamsand providing low-latency predictions.
• Fine-tune and optimize existing machine learning models to improve performance, scalability, and efficiency.
• ConductA/B testing and model validationto measure the impact of deployed models.
• Implement robustmodel monitoring systemsto detect drift, bias, and performance degradation in production.
• Collaborate with Data Engineers to ensurehigh-quality, preprocessed datasetsfor training and inference.
• Stay informed aboutemerging trends in AI/ML, exploring new technologies and techniques for potential integration.
• Create comprehensivetechnical documentationfor models, pipelines, and experiments.

Requirements:

• Minimum3+ yearsof experience as aMachine Learning Engineer, Data Scientist, or related role.
• Excellent command of the English Language in all forms.
• Previous start-up experience would be an advantage. 
• Proficiency inPython, R, orScala, with experience usingML libraries and frameworks(e.g., TensorFlow, PyTorch, Scikit-learn).
• Experience with tools likeMLflow, Kubeflow, or similar platforms for managing ML pipelines.
• Hands-on experience withHadoop, Spark, ordistributed computing frameworks.
• Proficiency inSQL and NoSQL databasesfor accessing and preprocessing large datasets.
• Familiarity withcloud ML services(e.g., AWS SageMaker, GCP AI Platform, Azure ML).
• Experience deploying ML models inproduction environmentsusing tools likeDocker, Kubernetes, andCI/CD pipelines.
• Solid foundation inprobability, statistics, and experimental design.
• Strong ability to work cross-functionally withData Scientists, Engineers, andProduct Teams.
• Analytical mindset with excellent problem-solving and debugging skills.

Ideal Candidate Profile:

• Apassionate AI enthusiastwho thrives on building systems that bridge innovation and user experience.
• Strong communicator, capable of explainingcomplex ML conceptsto both technical and non-technical audiences.
• Adaptable and excited about solvingreal-world problemswith AI and machine learning.
• Detail-oriented, with a strong focus on buildingscalable, efficient, and robust ML systems.
• Continuously curious aboutcutting-edge AI technologiesand eager to experiment with new approaches.
• Collaborative mindset with the ability towork across teams and drive alignment.

Compensation & Benefits

Equity-only at present, to transition to a salaried, full-time permanent position when funding is secured.

Remote and flexible working arrangements, the opportunity to be part of something potentially epic with potential opportunities for global travel, and access to industry conferences and workshops in due course.