Machine Learning Engineer - Equity Only
Machine Learning Engineer - Equity Only
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Job Description
PLEASE NOTE THIS IS AN EQUITYONLY ROLE AND THE INTERVIEWS WILL COMMENCE IN FEBRUARY 2025.
StealthMode StartUp Client is seeking a skilled Machine Learning Engineer to design build and deploy AI/ML models that power personalized recommendations predictive analytics and realtime data insights on a global platform. This role will focus on developing machine learning pipelines finetuning algorithms and ensuring scalable deployment of AIdriven features across both web and mobile environments.
The ideal candidate will have a strong background in machine learning data science and software engineering with experience in building and deploying scalable 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 deploy machine learning models for tasks such as user behaviour prediction content recommendations and fraud detection.
- Develop and maintain endtoend machine learning pipelines from data collection and preprocessing to model deployment and monitoring.
- Collaborate with Data Engineers and Product Teams to seamlessly integrate AI capabilities into product workflows.
- Build realtime ML systems capable of handling dynamic data streams and providing lowlatency predictions.
- Finetune and optimize existing machine learning models to improve performance scalability and efficiency.
- Conduct A/B testing and model validation to measure the impact of deployed models.
- Implement robust model monitoring systems to detect drift bias and performance degradation in production.
- Collaborate with Data Engineers to ensure highquality preprocessed datasets for training and inference.
- Stay informed about emerging trends in AI/ML exploring new technologies and techniques for potential integration.
- Create comprehensive technical documentation for models pipelines and experiments.
Requirements:
- Minimum 3 years of experience as a Machine Learning Engineer Data Scientist or related role.
- Excellent command of the English Language in all forms.
- Previous startup experience would be an advantage.
- Proficiency in Python R or Scala with experience using ML libraries and frameworks (e.g. TensorFlow PyTorch Scikitlearn).
- Experience with tools like MLflow Kubeflow or similar platforms for managing ML pipelines.
- Handson experience with Hadoop Spark or distributed computing frameworks.
- Proficiency in SQL and NoSQL databases for accessing and preprocessing large datasets.
- Familiarity with cloud ML services (e.g. AWS SageMaker GCP AI Platform Azure ML).
- Experience deploying ML models in production environments using tools like Docker Kubernetes and CI/CD pipelines.
- Solid foundation in probability statistics and experimental design.
- Strong ability to work crossfunctionally with Data Scientists Engineers and Product Teams.
- Analytical mindset with excellent problemsolving and debugging skills.
Ideal Candidate Profile:
- A passionate AI enthusiast who thrives on building systems that bridge innovation and user experience.
- Strong communicator capable of explaining complex ML concepts to both technical and nontechnical audiences.
- Adaptable and excited about solving realworld problems with AI and machine learning.
- Detailoriented with a strong focus on building scalable efficient and robust ML systems.
- Continuously curious about cuttingedge AI technologies and eager to experiment with new approaches.
- Collaborative mindset with the ability to work across teams and drive alignment.
Compensation & Benefits
Equityonly at present to transition to a salaried fulltime 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.
Employment Type
Full Time
