What are the responsibilities and job description for the Principal Architect - ML position at United Airlines?

Description

Find your future at United! We’re reinventing what our industry looks like, and what an airline can be – from the planes we fly to the people who fly them. When you join us, you’re joining a global team of 100,000 connected by a shared passion with a wide spectrum of experience and skills to lead the way forward.

Achieving our ambitions starts with supporting yours. Evolve your career and find your next opportunity. Get the care you need with industry-leading health plans and best-in-class programs to support your emotional, physical, and financial wellness. Expand your horizons with travel across the world’s biggest route network. Connect outside your team through employee-led Business Resource Groups.

Create what’s next with us. Let’s define tomorrow together.

United's Digital Technology team is comprised of many talented individuals all working together with cutting-edge technology to build the best airline in the history of aviation. Our team designs, develops and maintains massively scaling technology solutions brought to life with innovative architectures, data analytics, and digital solutions.

Job overview and responsibilities :

United Airlines is seeking dedicated people to join the Data and Machine Learning Engineering team. The organization dedicated towards leading data driven insights & innovation to support the ML / AI needs for commercial and operational projects with a digital focus. This resource will frequently collaborate with ML engineers, data scientists and data engineers. This role will build, architect, implement and lead key components of the Machine Learning Platform, Gen AI / ML business use cases, and establish efficient processes and standard methodologies.

Build high-performance, cloud-native machine learning infrastructure and services to enable rapid innovation across United. Set up containers and Serverless platform with cloud infrastructure.
Build and develop tools and apps to enable ML automation using AWS ecosystem
Build data pipelines to enable Machine Learning models for batch and real-time data
Provide outstanding hands-on development expertise on Spark and Flink for both real time and batch applications
Improve and support large scale model training and serving pipelines in distributed and scalable environment.
Stay aligned with the latest developments in cloud-native and ML ops / engineering and to experiment with and learn new technologies – NumPy, data science packages like sci-kit, microservices architecture
Perform performance evaluations of the LLM models, Implement LLMOps processes to run the end-to-end lifecycle of LLM's
Build, optimize, fine-tune Generative AI / LLM models to improve performance and accuracy and deploy them

Qualifications

What’s needed to succeed (Minimum Qualifications) :

Bachelor's degree required in Computer Science, Data Science, Generative AI, Engineering or related subject area or Mathematics experience required

7 years of overall experience in machine learning, deep learning, and natural language processing

Outstanding software engineering experience with Python and at least one additional language such as Go, Java, or C / C

Outstanding technical leadership and efficient with data science methodologies and frameworks (, PyTorch, Tensorflow) and preferably building and deploying production ML pipelines

Experience in ML model life cycle development experience and prefer experience to variety of technical common algorithms the like XGBoost, CatBoost, Deep Learning, etc.

Experience setting up and optimizing efficient data stores (RDBMS / NoSQL) for production use in the ML app context

Outstanding Cloud-native DevOps, CI / CD experience using variety of technical tools such as Jenkins or AWS Code Pipeline; preferably experience with GitOps using ArgoCD, Flux, or Jenkins X

Experience with GEN AI models such as GANs, VAEs, and auto-regressive models

Prompt engineering : Ability to build and craft prompts that evoke desired responses from LLMs.

LLM evaluation : Ability to conduct performance evaluations on LLMs on a variety of tasks, including accuracy, fluency, creativity, and diversity

LLM debugging : Ability to identify and fix errors in LLMs, such as bias, informative errors, and logical inconsistencies

LLM deployment : Ability to deploy LLMs in production environments and ensure that they are reliable and secure

Outstanding experience within LLMOps (Large Language Model Operations) spearhead the end-to-end lifecycle of large language models

Outstanding experience with generative ai methods such as retrieval augmented generation (RAG) and instruction fine tuning

Must be legally authorized to work in the United States for any employer without sponsorship

What will help you propel from the pack (Preferred Qualifications) :

Master's / PhD degree in computer science or related STEM field combined with 5 additional years of experience working in cloud environments (AWS preferred) - Kubernetes, Dockers, ECS and EKS

Over 5 years of elevated experience with variety of technical Big Data technologies such as Spark, Flink and SQL programming

Apply for this job

Receive alerts for other Principal Architect - ML job openings

Principal Architect - ML

What are the responsibilities and job description for the Principal Architect - ML position at United Airlines?

What is the career path for a Principal Architect - ML?

Job openings at United Airlines

Not the job you're looking for? Here are some other Principal Architect - ML jobs in the Chicago, IL area that may be a better fit.

We don't have any other Principal Architect - ML jobs in the Chicago, IL area right now.

AI Assistant is available now!