The Role
We are looking for a (Senior-) Data Scientist who is excited to join us in building the first global supplier search. We believe that the Data Scientist plays a crucial role in the development of cutting-edge artificial intelligence-powered products, and collaborate across multiple teams to accomplish that. Your role will primarily involve framing business problems, researching and selecting advanced Natural Language Processing (NLP) machine learning models, and leveraging your expertise in data collection, processing, feature engineering, and production-ready solutions. You’ll be responsible for keeping track of the development of machine learning models to improve our products and aligning with the Product team regarding Data Science development goals. You will also have the opportunity to work with our Founders, Machine Learning Engineers, Data Engineers, and Software Engineers to understand the core business problems and provide the right solutions.
We mainly work with Python, VertexAI, Airflow, Docker, Flask, and Github CI/CD. We are open to using other technologies and are excited to expand our tech stack. In addition, we believe in learners with a growth mindset, so feel free to apply even if you don’t know all of these technologies.
What we offer
- Working in a fast-paced environment with challenging tasks (zero-boredom-guarantee)
- High ownership and the freedom to manage your own projects
- Direct collaboration with the founders – true flat hierarchy
- Rapid professional development & leadership opportunities with a steep learning curve
- Awesome team events and an inclusive company culture with a diverse team
Your responsibilities
- ML Training Workflow: Create and manage machine learning auto-training workflows, including data versioning, data processing, model training, model versioning, model evaluation, and testing using appropriate tools or platform
- Model Training: testing, experimenting, and implementing appropriate NLP ML algorithms, fine-tuning, training, retraining models, and staying updated with the latest developments in the field.
- Model Deployment and Optimization: Deploy machine learning models, optimize LLM/transformer models inference, and provision suitable infrastructure including distributed systems, GPU, and parallelization to achieve optimal cost and processing time. Expose models as APIs for integration with other services and software to serve Data Science to different functions.
- Collaboration: Collaborate closely with Data Scientists, Data Engineers, and Software Engineers to integrate machine learning models into scalable and reliable applications.
- Model Monitoring: Implement model integration and monitoring in the application to collect human feedback for retraining and improvements.
- Data Annotation/Collection System: Build and maintain data annotation and collection systems.
Your experience
- 3-5 years of experience as a Machine Learning Engineer/Data Scientist.
- Familiarity with machine learning frameworks (like TensorFlow or PyTorch) and libraries (like scikit-learn, pandas, numpy)
- Experience in deploying models in production environments and understanding of infrastructure.
- Proficiency in Python, Docker, CI/CD, Google VertexAI (or similar), Airflow, and Kubernetes and code version control (e.g., Git)
- Experience in building and maintaining production data pipelines at scale, which are integral to or driven by machine learning models in production.
- Sound understanding of the machine learning product lifecycle and its associated components, including DataOps/Pipelines, Model Deployment, Testing, Monitoring, and model repositories,…
- Strong experience in developing APIs for the effective serving of machine learning models or the capability to prepare models for seamless integration.
- Understanding of NLP models, with a data science background/experience in NLP, would be a plus.
- Proven capability to work effectively in small teams within fast-paced environments.
- Any experience in procurement, logistics, or manufacturing would also be a plus.
What we value
- Honest, fast, and open collaboration as well as strong communication skills
- Resourceful self-starters who hold themselves to high standards, have
attention to detail, are intrinsically motivated & eager to learn on a daily basis
- Proactive hands-on working style with a passion for customer-facing tasks
- Team members who are excited about our mission & tech
- Shared success through stock options and competitive salaries
If you’re an expert data scientist who loves greenfield projects, we’d love to talk to you!
Alpas is proud to be an equal-opportunity employer. We view diversity as a moral imperative and competitive advantage. We are committed to equal employment opportunities regardless of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. If you have a disability or special need that requires accommodation, please let us know.
