3 publicaciones de empleo destacadas de machine learning en querétaro, que (¡Están contratando!)

Machine Learning Engineer
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- Azure
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Data Engineer
Harman International —Querétaro, Qro.
- Azure
- Informática
- Inglés
- Descuento de empleados

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Machine Learning Engineer

Harman International -
Querétaro, Qro.

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Información del empleo

Beneficios

Descuento de empleados

Cualificaciones

TensorFlow
Azure
Informática
Procesamiento de señales digitales
PyTorch
NumPy
Maestría
Pandas
C++
Docker
Licenciatura
SciPy
S3
Linux
Recolección de datos
Python

Descripción completa del empleo

Location:

Queretaro - Queretaro, Mexico - Avenida 5 de Febrero

Job Family:

Artificial Intelligence & Machine Learning

Worker Type Reference:

Regular - Permanent

Pay Rate Type:

Salary

Career Level:

Job ID:

R-51833-2026

Description & Requirements

Introduction: A Career at HARMAN Automotive

We’re a global, multi-disciplinary team that’s putting the innovative power of technology to work and transforming tomorrow. At HARMAN Automotive, we give you the keys to fast-track your career.

Engineer audio systems and integrated technology platforms that augment the driving experience
Combine ingenuity, in-depth research, and a spirit of collaboration with design and engineering excellence
Advance in-vehicle infotainment, safety, efficiency, and enjoyment

About the Role

As an ML Engineer on the Innovation Team, you will design and operate end-to-end machine learning systems that continuously improve in-vehicle audio and infotainment experiences. You will transform raw and in-field data into production-ready solutions and ensure seamless integration, monitoring, and iteration of models deployed on embedded platforms.

You will participate in the full lifecycle from training to inference, collaborating with Data Scientists, DSP Engineers, and Audio Experts to design models and audio features. Your main responsibilities include ensuring optimal model performance on embedded devices and enabling remote updates to provide continuous improvements based on new training data or enhanced features.

You will enable a closed-loop system by integrating telemetry, model performance monitoring, and continuous retraining or system improvements based on real-world usage. While adhering to strict privacy, safety, and reliability requirements.

What You Will Do

Deploy ML models on embedded devices such as ARM processors, GPUs, NPUs, SHARC, and other DSP architectures.
Optimize models for edge hardware (e.g., quantization, pruning, distillation) to ensure real‑time execution within strict latency, memory, and compute budgets.
Collaborate with Data Scientists and DSP Engineers to convert research notebooks into robust, testable training and inference code; define evaluation criteria, acceptance thresholds, and quality guardrails.
Build end-to-end ML systems, including telemetry ingestion from vehicles, data validation, feature processing, training, evaluation, packaging, and deployment to production environments.
Implement continuous training and continuous deployment (CT/CI/CD for ML) with full traceability of model and version registries, along with safe rollback mechanisms.
Partner with Embedded DSP Engineers to ensure real‑time execution performance, leveraging hardware accelerators such as SIMD, MMA or NEON units.
Estimate and measure model‑footprint metrics (CPU utilization, memory usage, latency, etc.).
Redesign or restructure model architectures to reduce embedded resource consumption while maintaining similar levels of accuracy and overall model performance.
Collaborate on OTA and data‑collection strategies to support continuous model improvement while adhering to strict privacy constraints.
Contribute to internal documentation, reusable components, and best practices; mentor peers on MLOps workflows and edge optimization techniques.
Implement monitoring systems to track model performance, data drift, and system behavior in production, ensuring reliability and continuous improvement based on real-world usage.
Design and implement monitoring systems to track model performance, data drift, and system behavior in production, ensuring reliability and continuous improvement based on real-world usage.
Provide guidance to less‑experienced team members on model deployment strategies and automation of ML pipelines.

What You Need to Be Successful

Ability to work in rapid prototyping environments; self‑driven, fast learner, with a strong passion for innovation and problem solving with strong sense of ownership to reach goals on time.
Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Machine Learning, Signal Processing, or a closely related field.
5+ years of end‑to‑end ML development experience, including model training, optimization, deployment, and monitoring.
Proficiency in C/C++ programming language for embedded systems
Practical experience deploying models on embedded devices such as ARM Cortex cores, GPUs, NPUs, and DSPs (e.g., SHARC).
Experience building MLOps pipelines, including automated training jobs, dataset versioning/switching, model optimization workflows, and unit tests for ML code.
Strong understanding of real‑time systems execution constraints (scheduling, interrupts, shared‑core resource).
Strong proficiency in Python and production‑grade machine learning using frameworks such as TensorFlow, PyTorch, scikit‑learn, NumPy, and Pandas.
Experience with MLOps practices and CI/CD automation for ML model delivery.
Experience working with data lakes and cloud data platforms (AWS S3, Azure, Databricks, etc.) for storage, processing, and training pipelines.
Expertise in edge model optimization techniques including quantization (dynamic and post‑training), pruning, model compression, and mixed‑precision execution.
Working knowledge of privacy‑preserving data handling (pseudonymization, anonymization, etc.), data‑quality checks, and data‑lineage tracking.
Strong communication and collaboration skills, with the ability to work effectively in an intercultural and cross‑functional team.
Proven ability to write unit tests, integration tests, and performance benchmarks for ML models and data pipelines.

Bonus Points if You Have

Experience working with audio, image or signal processing domains
Experience building data collection architecture design and overall Data Engineering infrastructure
Experience working with automotive platforms such as Android Automotive OS, QNX, and embedded Linux.
Understanding of audio‑hardware communication protocols such as TDM and I²S.
Experience profiling and optimizing models on SoC or DSPS (Qualcomm, NXP, TI, NVIDIA SHARC, TI)
Applied knowledge of audio signal processing such as STFT, mel‑spectrogram features, and filtering and experience using python audio libraries like Librosa, SciPy, or PyAudio.
Familiarity with OTA update flows, artifact versioning, and safe rollback mechanisms.
Experience building reproducible working‑environment (docker, virtual environments)
Proven experience with formal software‑development processes and the Scrum framework.
Experience connecting data cloud services directly on python

What Makes You Eligible

Ability to work from an office in Queretaro, 3+ days per week (hybrid)
Because the team operates globally, flexibility in working hours is required.
Successfully complete a background investigation and drug screen as a condition of employment

What We Offer

Access to employee discounts on world-class Harman and Samsung products (JBL, HARMAN Kardon, AKG, etc.)
Extensive training opportunities through our own HARMAN University
Competitive wellness benefits
Tuition reimbursement
“Be Brilliant” employee recognition and rewards program

#LI-KV2

About HARMAN: Where Innovation Unleashes Next-Level Technology

Ever since the 1920s, we’ve been amplifying the sense of sound. Today, that legacy endures, with integrated technology platforms that make the world smarter, safer, and more connected.

Across automotive, lifestyle, and digital transformation solutions, we create innovative technologies that turn ordinary moments into extraordinary experiences. Our renowned automotive and lifestyle solutions can be found everywhere, from the music we play in our cars and homes to venues that feature today’s most sought-after performers, while our digital transformation solutions serve humanity by addressing the world’s ever-evolving needs and demands. Marketing our award-winning portfolio under 16 iconic brands, such as JBL, Mark Levinson, and Revel, we set ourselves apart by exceeding the highest engineering and design standards for our customers, our partners and each other.

If you’re ready to innovate and do work that makes a lasting impact, join our talent community today!

Important Notice: Recruitment Scams

Please be aware that HARMAN recruiters will always communicate with you from an '@harman.com', ‘@careers.harman.com’ or ‘@harmanglobal.avature.net’ email address. We will never ask for payments, banking, credit card, personal financial information or access to your LinkedIn/email account during the screening, interview, or recruitment process. If you are asked for such information or receive communication from an email address not ending in one of the above email domains about a job with HARMAN, please cease communication immediately and report the incident to us through: [email protected].

You Belong Here

HARMAN is committed to making every employee feel welcomed, valued, and empowered. No matter what role you play, we encourage you to share your ideas, voice your distinct perspective, and bring your whole self with you – all within a support-minded culture that celebrates what makes each of us unique. We also recognize that learning is a lifelong pursuit and want you to flourish. We proudly offer added opportunities for training, development, and continuing education, further empowering you to live the career you want.

HARMAN is proud to be an Equal Opportunity employer. HARMAN strives to hire the best qualified candidates and is committed to building a workforce representative of the diverse marketplaces and communities of our global colleagues and customers. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. HARMAN attracts, hires, and develops employees based on merit, qualifications and job-related performance.(www.harman.com)

HARMAN is committed to providing reasonable accommodations to applicants with disabilities. If you need assistance or an accommodation during the application process, please contact us at [email protected]. Requests will be considered on a case-by-case basis in accordance with applicable law.

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