Sr. Machine Learning Engineer

Ford Motor Company; Naucalpan de Juárez; Presencial; USD 60,000 - 90,000; Jornada completa

Descripción de la vacante

A leading company in the automotive sector seeks a seasoned Machine Learning Engineer to analyze complex data and provide actionable insights. The role entails working within a dynamic environment, fostering collaboration with business partners, and applying cutting-edge ML techniques to address real-world challenges.

Formación

• 4+ years of experience with software engineering best practices.
• 2+ years working within public cloud ecosystems.
• Strong technical writing and oral communication skills.

Responsabilidades

• Analyze and manipulate high-volume, structured and unstructured data.
• Apply AI and Machine Learning to solve complex problems.
• Communicate and present models to business stakeholders.

Conocimientos

Python

Machine Learning

Data Analysis

Statistical Modeling

Cloud Computing

Data Visualization

Educación

Master’s or Ph.D. in Computer Science, Operational Research, Statistics, Applied Mathematics

Herramientas

AWS

GCP

Azure

Docker

PostgreSQL

MySQL

TensorFlow

PyTorch

Descripción del empleo

Potential candidates should have excellent depth and breadth of knowledge in machine learning, data mining, and statistical modeling. They should possess the ability to translate a business problem into an analytical problem, identify the relevant data sets needed for addressing the analytical problem, recommend, implement, and validate the best suited analytical algorithm(s), and generate/deliver insights to stakeholders. Candidates are expected to regularly refer to research papers and be at the cutting-edge with respect to algorithms, tools, and techniques. The candidate is expected to provide hands-on contributions to projects while providing mentorship to more junior team members and interacting with Business partners on a regular basis.

Job Qualifications:

• Master’s or Ph.D. degree in Computer Science, Operational Research, Statistics, Applied Mathematics, or in any other engineering discipline preferred.
• 4+ years of experience with software engineering best practices in a team of 6+ engineers.
• 2+ years working within public cloud ecosystems (AWS, GCP, or Azure).

Technical Skills:

• Strong programming skills in Python.
• Expertise in designing & architecting cloud-based data pipelines / microservices.
• Experience working with relational (PostgreSQL, MySQL), NoSQL, and columnar databases like BigQuery.
• Proficiency in building, deploying, and managing applications using Docker containers.
• Experience in feature engineering, hyperparameter tuning, model evaluation, etc.
• Experience with Pandas/Numpy/ScikitLearn, Pytorch, TensorFlow, Huggingface.
• Knowledge of modern NLP or Computer Vision modeling techniques.
• Familiarity with deep learning best practices.
• Strong technical writing and oral English skills.

Preferred Qualifications:

• Git and GitHub best practices.
• Test and Behavior Driven Development.
• Linux shell scripting.
• Experience with Google Cloud Platform.
• Experience with front-end/back-end technologies (React, Angular, Node.js).
• Proficiency in Infrastructure-as-Code tools, specifically Terraform.
• Knowledge of CI/CD pipelines and automation frameworks.

Leadership Skills:

• Ability to build and lead high-performing engineering teams.
• Understanding of security best practices and data governance.
• Problem-solving and troubleshooting skills.
• Excellent communication and collaboration skills.
• Experience delivering complex projects under tight deadlines.
• Experience in manufacturing or automotive sectors preferred.

Ford Motor Company is an Equal Opportunity Employer, committed to a diverse workforce, and does not discriminate based on race, color, sex, age, national origin, religion, sexual orientation, gender identity, veteran status, or disability.

Responsibilities:

• Analyze source data and data flows, working with structured and unstructured data (text, audio, images, video, etc.).
• Manipulate high-volume, high-dimensionality data to expose patterns, anomalies, relationships, and trends.
• Apply AI and Machine Learning to solve complex, real-world problems.
• Analyze and visualize data, interpret results in a business context, and report findings clearly.
• Provide ML consulting for problem formulation and technique selection.
• Communicate and present models to business and executive stakeholders.
• Collaborate with business partners and present results effectively.