ML Engineer

Key Skills

Aartificial intelligence, Ansible, AWS, Azure, Bamboo, Continuous Integration & Continuous Delivery - CI/CD, Docker, Effective communication skills, Google Cloud Platform (GCP), Infrastructure as code, Java Programming, Jenkins, Kubernetes-K8s, Machine learning techniques, Pandas, Python Programming, PyTorch, Scala Programming, Scikit-learn, Terraform

Job Description

This position is in the IBM The Weather Company business (TWC) or a shared services function supporting TWC. On August 22 2023, a definitive agreement was signed, under which Francisco Partners, a leading global investment firm that specializes in partnering with technology businesses, will acquire The Weather Company assets from IBM. It is currently expected that as of February 1, 2024, this position will be in a new company that is separate from IBM. Through increased investment and resources from Francisco Partners, The Weather Company will look to move beyond forecasting alone and bring new tools and experiences to users to help them understand how weather impacts all aspects of their lives, starting with health and well-being. For businesses, The Weather Company plans to offer more actionable insights so organizations can provide greater value to their customers. With its advertising platform, The Weather Company will continue to provide quality real-time experiences for the ad and subscription media industry, while complying with all consumer privacy laws and regulations. Don’t miss your opportunity to influence the future of our company!

Your Role and Responsibilities

We are looking for a talented and passionate ML Engineer – Feature Engineering to join our AI team. Our mission is to build predictive solutions that focus on the business needs of IBM Cloud and Cognitive Software, Watson Advertising and Weather. These include solutions like the IBM Weather Channel app for recommendations based on user activity.

You will be working closely with each team member to understand the team’s overall strategy and direction and provide your ML expertise in collaborating to design, build, deploy, and operate production pipelines and systems.

The ideal candidate will be:

Problem solver: you excel at understanding and solving complex problems in a proactive way.

Quality communicator: you can break down complex or difficult topics and present these verbally, and in writing

Ownership: you love being responsible for owning and improving AI solutions

Sharing: you’re excited by the opportunity to establish best practices for the team through leading by example and promoting culture change

Curiosity: you are innately curious, and have a passion for learning new things

Passionate: you have a passion for all things AI and ML and want to share that with the team

This person will:

1. Implement end to end feature engineering pipeline to productionize ML features provided by data scientists

2. Ensure data quality checks are added and that quality of features in production is maintained

3. Implement end-to-end solutions for batch and real-time algorithms along with requisite tooling around monitoring, logging, automated testing, performance testing and A/B testing

4. Identify new opportunities to improve business processes and improve consumer experiences, and prototype solutions to demonstrate value with a crawl, walk, run mindset.

5. Work with data scientists and analysts to create and deploy new product features on the Weather Channel website and the Weather Channel mobile apps

6. Establish scalable, efficient, automated processes for data analyses, model development, validation and implementation

7. Write efficient software to ship products in an iterative, continual-release environment

8. Contribute to and promote good software engineering practices across the team

Required Technical and Professional Expertise

• Bachelor’s degree in a STEM field such as Statistics, Math, Engineering, Information Systems, etc.
• Strong knowledge of deploying and maintaining ML pipelines in production
• Experience with Apache spark
• In depth knowledge of machine learning frameworks like: Scikit-Learn, Pandas, PyTorch, etc.
• Deep experience with Docker and containerization.
• Strong experience with Kubernetes and container orchestration platforms.
• Strong experience with Python, Java, Scala, or Go development.
• Deep experience with cloud platforms (e.g., IBM Cloud, AWS, GCP, and/or Azure) with particular experience with ML & Data offerings operating and deploying solutions using AWS Service including, but not limited to, S3, EKS, EMR, Athena, Glue, Lambdas, Athena, Kinesis, MSK, Sagemaker, SQS and SNS (or correlated offerings on other cloud platforms).
• Deep experience with CI/CD tools (e.g., Jenkins, TravisCI, Bamboo).
• Good communication and presentation skills to explain technical solutions to either technical peers or non-technical stakeholders.

Preferred Technical and Professional Expertise

• Master’s degree in a STEM field such as Statistics, Math, Engineering, Information Systems, etc.
• 1 – 3 years of work experience with infrastructure-as-code (e.g., Terraform, Ansible, Chef).
• 5 -7 years of work experience with cloud platforms such as IBM Cloud, AWS, GCP, and/or Azure.