Machine Learning Engineer - Mexico

Key Skills

Aartificial intelligence, Amazon EMR, Amazon RedShift, Apache Airflow, AWS Kinesis, AWS Sagemaker, Databricks, Deep Learning, Digital Marketing, Docker, Google Cloud Platform (GCP), Keras software library, Kubernetes-K8s, Lambda, Machine learning techniques, MLOps tools, Neural Networks, Snowflake, TensorFlow

Job Description

ML Engineer within the Data and Identity Applied Science and Machine Learning team leverages Acxiom and third-party software to create solutions to business problems defined by specific business requirements. In this position, you will draw upon technical, ML engineering, Data and MLOps experience to solve complex marketing analytics problems on very large volumes of data.

As a Machine Learning (ML) Engineer You will build and operationalize machine learning pipelines involving terabytes of data. You will have the responsibility to help define requirements, create software designs, implement code to these specifications.

As an ML Engineer, you will be expected to:

• Work with Applied Scientists, Data Scientists, Product owners, ML Engineers, and Software Engineers to design and deliver ML solutions in production at scale.
• Develop ML workflows and end-to-end pipelines for data preparation, training, deployment, monitoring, etc., and ensure the quality of architecture and design of our ML systems and data infrastructure.

Location: Lomas Atlas, Mexico City, MX

Qualifications

Experience Required

• Bachelor’s Degree in Computer Science or equivalent experience to a Bachelor's degree
• 2+ years professional experience in software development
• Computer Science fundamentals in object-oriented design
• Computer Science fundamentals in data structures
• Computer Science fundamentals in algorithm design, problem solving, and complexity analysis
• Knowledge of, at least, one modern programming language such as Java, C++, C, Java, or Perl
• Good communication skills: communicate ideas clearly and effectively to other members of the analytics team and to the client at multiple levels (both technical and business)
• Proficient English Speaking and Writing

Preferred Experience

• 3+ years of experience building scalable ML infrastructure and big data systems.
• Experience successfully mentoring junior ML Engineers.
• High attention to detail and proven ability to manage multiple, competing priorities simultaneously.
• Experience MLOps and orchestration tools such as Airflow, Kubeflow, Optuna, BentoML or similae tools.
• Proficiency with Apache Spark, EMR/DataProc and Cloud based tools (Snowflake, Redshift, EMR, Glue, Step Functions, Lambda, Step functions, AWS Batch, or similar etc.).
• Experience with ML libraries and deep learning frameworks (PyTorch, TensorFlow, etc.).
• Experience with end-to-end software development and life cycle of ML solutions.
• Analytic problem-solving skills with the ability to think outside-the-box
• Analytical thinker that excels at analyzing and understanding data to answer questions
• Excellent understanding of data concepts, data architecture, data manipulation/engineering, and data engineering design
• Passion for considering how projects fit into the wider business picture
• An understanding in multiple types of programming languages in order to be adaptable (statically typed vs. dynamically typed and object-oriented vs. procedural)
• Self-Starter – Able to work independently with little guidance
• Adaptable - Able to adapt to diverse technical challenges and systems
• Ability to formulate and present insights with gathered data to both technical and non-technical peers, leaders, and clients

What will set you apart

• Experience in CI/CD/DevOps, Deployment and Automation Tool – CI/CD, Jenkins, Terraform, Cloud Formation Template or similar