Sales - Machine Learning Engineer, AIOps

Key Skills

Aartificial intelligence, AIOps, Apache Airflow, AWS, Azure, Big Data Technology, Continuous Integration & Continuous Delivery - CI/CD, Google Cloud Platform (GCP), Grafana, Machine learning techniques, PyTorch, Sales, TensorFlow

Job Description

In this role, you will focus on the following key areas:

• Model Management: Oversee the deployment, maintenance, and scaling of LLM, and services within our consumer-facing products.

• CI/CD: Build and maintain CI/CD pipelines to automate model train/test/deployment and scaling.

• Collaborative Integration: Partner with product developers, UX designers, and data scientists to ensure a seamless and intuitive integration of language models into our products.

• Continuous Monitoring: Build Dashboard and Regularly track model performance, ensuring consistent accuracy and reliability for consumers. Set up alerts and manage the type of monitoring needed.

• Feedback Integration: Develop strategies for collecting user feedback and refining the model for better alignment with consumer needs.

• Bias Mitigation: Proactively address and reduce potential biases in model predictions, ensuring our products are inclusive and fair.

• Infrastructure Management: Design and implement efficient data pipelines to support large language model training and inference

• Documentation: Maintain comprehensive documentation covering model versions, deployment protocols, and performance metrics.

• Research & Development: Stay updated with the latest trends in large language models and MLOps, ensuring our consumer products remain at the forefront of innovation.

Minimum Qualifications

• M.S. in related field with 3+ years experience applying AIOps machine learning engineer to real business problems.
• Language Model Expertise: Demonstrated experience working with large language models, such as OpenAI's GPT series or similar.
• MLOps Skills: Solid background in Automating ML pipeline, including the training, testing, deployment, monitoring, and scaling of AI models.
• Technical Toolkit: Proficiency in PyTorch, TensorFlow, Transformers, Kubernetes, Docker, LangChain, vectorDB and cloud platforms like AWS, GCP, or Azure, and Monitoring tool like Grafana, and CI/CD like airflow, gitlab, and Big Data management like Spark, Kafka.
• Product-Centric Mindset: Proven track record of integrating AI models into consumer products, enhancing functionality, and user experience.

Preferred Qualifications

• Communication Prowess: Excellent communication skills, with the ability to liaise between technical and non-technical teams.
• Collaborative Spirit: Experience in cross-functional teams, ensuring seamless product development.