Applied ai researcher, mlops

We are seeking an exceptional Applied AI Researcher-MLOps to join us in shaping the future of Generative Artificial Intelligence (GenAI). We are looking for a researcher with a proven track record of building tools that enable large cutting-edge research and product solutions. As a member of our Applied Research team, you will play a critical role in bridging the gap between data science and engineering, enabling our AI models to be deployed efficiently and reliably. You will work closely with our data scientists, software engineers, and product teams to design, implement, and maintain our MLOps pipelines, ensuring seamless model deployment, monitoring, and maintenance. This position offers exciting opportunities to work closely with cross-functional teams and external partners to drive innovations in enterprise-grade GenAI.

Duties and Responsibilities: 

• Subject matter expertise: Design, develop, and maintain pipelines for data (crawling, cleaning, and processing) and models (deploying, monitoring, and updating);

• Model Deployment: Design, implement, and manage the deployment pipelines for AI/ML models, ensuring they meet performance and reliability standards in production;

• Infrastructure Management: Develop and maintain the infrastructure required for deploying and scaling AI/ML models, including cloud services, container orchestration (e.g., Kubernetes), and CI/CD pipelines;

• Monitoring and Optimization: Implement monitoring and logging systems to track the performance of models in production, identify bottlenecks, and optimize model performance and resource utilization.

• Team work:

  • Collaborate with cross-functional teams, including Product Technology, Engineering, Quality Assurance, and Customer Success, to seamlessly incorporate innovation and maintain our product technology leadership;

  • Participate in high-level technical discussions, contributing to technology assessment and roadmap planning;

  • Mentor and guide junior team members and help building a strong culture of rapid innovation;

• Continuously stay abreast of emerging trends and advancements in of GenAI and associated fields, while disseminating appropriate research results at top-tier conferences and journals.

To be successful in this role, it is essential to have knowledge and/or experience in: 

• Education: BSc or MSc degree in Computer Science, Data Science/Machine Learning, or a related field;

• Professional experience: 2+ years in MLOps, DevOps, or related roles deploying machine learning models in production environment.

Core technical skills:

• Cloud Platforms: AWS, Azure, GCP;

• Development: Python, PyTorch, Keras, Julia, Go, CI/CD pipelines, and version control;

• ML Platforms: MLflow, Kubeflow, TFX (TensorFlow Extended), serving platforms (gRPC, ONNX, JIT);

• Monitoring: Prometheus, Grafana, ELK Stack;

• Container/Orchestration: Docker, Kubernetes, Docker Swarm, RabbitMQ;

• Theoretical foundation: deep learning, traditional machine learning, probability and statistics, natural language processing, computer vision, data wrangling and preparation, and model evaluation and interpretation;

• Programming Skills: Proficiency in programming languages such as Python and experience working with version control systems (e.g., Git) and collaborating on code repositories is crucial.

It would be nice/it s a plus if you know/have experience in:

• 3+ years of hands-on experience as an MLOps Engineer;

• Experience developing tools, libraries, and infrastructure for data preprocessing, model training/finetuning, and deployment of LLMs in research and production environments.

• Technology stack:

  • Infrastructure as Code (IaC): Terraform, CloudFormation, Ansile, etc.

  • Configuration Management: Ansible, Puppet, Chef;

  • Frameworks: Django, Flask, OpenAPI, FastAPI, Spring Boot, Express.js;

  • Databases: PostgreSQL, MySQL, MongoDB, Redis.

Benefits:

• Medical insurance (SulAmérica) - adding dependents will incur an additional charge;

• Meal Voucher credited at Flash Card;

• Life Insurance.

We ll be happy to look at your application

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