What will you be doing?
- Design, develop, and maintain machine learning pipelines for internal and client-driven projects.
- Deploy machine learning models, including pre-trained models (e.g., LLMs), into production environments and ensure scalability and performance.
- Collaborate with data scientists to translate models into production-ready systems that meet business requirements.
- Optimize and tune machine learning models for performance, reliability, and cost-efficiency.
- Integrate machine learning models with cloud platforms and other infrastructure (e.g., AWS, GCP, Azure).
- Implement model monitoring, logging, and maintenance systems to ensure continuous operation and improvement of deployed models.
- Work closely with software engineering teams to ensure seamless model integration into larger applications.
- Stay up to date with the latest advancements in machine learning engineering, infrastructure, and deployment technologies.
What do we need from you?
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field. Ph.D. is a plus.
- 3+ years of experience in machine learning engineering, software engineering, or a related role.
- Strong programming skills in Python, Java, or similar languages, with proficiency in ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Hands-on experience with deploying pre-trained models, such as Large Language Models (LLMs), into production environments.
- Experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes).
- Solid understanding of data pipelines, ETL processes, and version control systems (e.g., Git).
- Experience in building scalable, distributed systems and optimizing machine learning models for performance.
- Familiarity with MLOps tools and practices, including model versioning, monitoring, and CI/CD pipelines.
- Strong communication skills and ability to collaborate with cross-functional teams, including data scientists and engineers.
What do you get in return?
- Love your career: Competitive total rewards package with excellent take home salaries, shifted work time bonus (if applicable) and an annual bonus plan!
- Love your development: Hone your skills or learn new ones with an annual training allowance; 2 paid professional development days, attend conferences, become certified, whatever you like!
- Love your work/life balance: 3 weeks of paid time off and flexible working hours. All you need is a stable internet connection!
- Love your workspace: We give you all the equipment you need to work from home including a laptop with your choice of OS, and budget to personalize your work environment!
- Love your community: Blog during work hours; take a day off and volunteer for your favorite charity.
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