MLOps Engineer

Responsibilities:

• Initiative & Collaboration: Take on high-level tasks with Data-Scientist or Project Leads.
  
• Develop strategies and operational plans independently.
  
• Translate high-level tasks into structured plans, complete with proof-of-concept models.
  
• Machine Learning Model Management: Implement, manage, and monitor the entire lifecycle of machine learning models. This includes their development, deployment, versioning, delivery, and archiving.
  
• Infrastructure & Pipeline Development-Deployment: Build and maintain infrastructure for model training, validating, deploying, and monitoring ML models.
  
• Develop robust data pipelines for large-scale, real-time and batch data processing.
  
• CI/CD-CT Automation and Tool Development: Automate repetitive tasks in the ML lifecycle. Develop and maintain tools to assist data scientists in model creation and improvement. Associate CI/CT strategies for model-training, model-testing with Verification & Validation teams.
  
• Technological Expertise: Stay abreast of the latest developments in MLOps technologies and integrate relevant advancements into our processes. Use strong analytical skills to identify and address issues in our MLOps processes and systems, improving efficiency and effectiveness.
  
• Stakeholder Communication: Effectively communicate technical information and project updates to stakeholders at various levels within the organization.
  

• Proven experience in MLOps, Data Engineering, or a similar role with a demonstrated capacity to work autonomously and take initiative.
  
• Deep understanding of machine learning algorithms and data science principles. Experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-Learn.
  
• Proficiency in developing and maintaining CI/CD pipelines, particularly those involving machine learning workflows.
  
• Proficiency in Python and familiarity with data manipulation/analysis libraries like pandas, NumPy, and SQL databases.
  
• Proficiency with cloud platforms such as AWS/EC2, GCP, or Azure and containerization tools like Docker, Kubernetes.
  
• Strong problem-solving skills with a track record of addressing and resolving complex technical issues.
  
• Excellent communication skills with the ability to explain complex technical concepts clearly.
  
• Bachelor s degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent work experience.
  
• Nice to have - Masters degree in data analyst, AI/ML, data engineering.
  
• Good to have experience with PaLM, LLaMA models, (E.g. optimizations with 7B, 13B, 33B, and 65B parameters), Previous experience with LAMDA. HumanEval etc.
  

• Additional free health insurance: Upgrade your current statutory health insurance plan after the probation period to ensure comprehensive coverage for you and your familys well-being.
  
• Generous vacation policy: Enjoy a generous allocation of 10 days of vacation per year, allowing you to recharge, spend quality time with loved ones, and pursue personal interests.
  
• Flexible working hours: Embrace our hybrid work model, where you can enjoy the best of both worlds. With 3 days in the office and 2 days working from home, you can tailor your schedule to suit your needs and achieve a healthy work-life balance.
  
• Open fridge & generous snack policy: Fuel your productivity and satisfy your cravings with our open fridge and generous snack policy. Enjoy a wide variety of refreshments and snacks to keep you energized throughout the day.
  

At L4B Software, we believe in providing our employees with a comprehensive compensation and benefits package that goes beyond the standard offerings. We value your well-being, work-life balance, and personal growth, and strive to create an environment where you can thrive both personally and professionally.

Join our team and experience the difference. Apply now and take the first step towards a rewarding career with us. We look forward to welcoming you to our team!

Please note that we cannot sponsor a work permit for United States - candidates eligible must already be located in United States, as we do not provide relocation assistance to candidates.