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Machine Learning Engineer (LLM Focus) Job Opening In Chile, Chile – Now Hiring KLog.co


Job description

$1,700.00/mo - $2,000.00/mo

Sobre el desafío

Somos la principal compañía tecnológica para el transporte internacional de carga en Latinoamérica, que a través del talento y tecnología, hemos logrado entregar visibilidad completa y control del proceso de importaciones y exportaciones a más de 5,000 clientes.

Trabajamos constantemente para brindar a nuestros clientes información precisa y actualizada sobre su carga en nuestra plataforma digital: dónde está, cuándo llega, cuál es el siguiente paso.

También brindamos asesoramiento basado en datos para que optimicen su cadena de suministro y reduzcan los riesgos.

Machine Learning Engineer / Área Tecnología

Actualmente nos encontramos en la búsqueda de un nuevo talento para nuestra área Tecnología como Machine Learning Engineer.

El equipo Tecnología de KLog.co se encarga de materializar la innovación tecnológica de la empresa, combinando experiencia logística con excelencia en desarrollo de software.

Funciones del cargo

  • Diseñar y desarrollar aplicaciones de punta a punta basadas en IA, utilizando técnicas como RAG, fine‑tuning y prompt engineering.

  • Evaluar y asegurar la calidad de modelos de lenguaje a través de métricas cuantitativas (como ROUGE) y evaluación cualitativa (coherencia, detección de alucinaciones).

  • Investigar nuevas herramientas y avances del ecosistema de IA para mejorar continuamente los productos y procesos internos.

  • Realizar análisis de datos para extraer insights accionables que aporten valor al negocio y optimicen el rendimiento de las aplicaciones.

  • Documentar procesos técnicos y generar guías de uso para facilitar la transferencia de conocimiento y el trabajo colaborativo.

¿Qué no puede faltar?

  • Programación y Ecosistema de Datos: sólida experiencia en Python y su ecosistema para Data Science, incluyendo librerías de manipulación de datos como Pandas y NumPy, y frameworks de deep learning como PyTorch o TensorFlow.

  • Fundamentos Cuantitativos: bases sólidas en estadística y probabilidad, con la capacidad de aplicar estos conceptos para el análisis exploratorio de datos y la interpretación y validación de resultados de modelos de IA (pruebas de hipótesis, distribuciones estadísticas).

¿Qué buscamos?

  • Excelentes habilidades de programación.

  • Compromiso con la buena ingeniería de datos.

    Buscamos crear sistemas robustos, responsivos, bien documentados.

    Necesitamos una persona que reconozca el valor del dato limpio, preciso e informativo.

  • Actitud de aprendizaje.

    Queremos a una persona que no le tenga miedo a ninguna fuente de datos ni tecnología, siempre dispuesta a investigar, aprender y enseñar.

  • Orientación al impacto.

    Creemos firmemente que el ingeniero debe conocer de cerca los problemas que intentamos resolver para que las soluciones que damos hagan la diferencia.

    Buscamos personas que se involucren en las problemáticas del negocio.

Lo que suma más puntos

  • Experiencia con plataformas en la nube (AWS o Azure).

  • Conocimiento sobre bases de datos vectoriales (ej.

    Pinecone, ChromaDB, Weaviate).

  • Conocimiento de GIT para control de versiones.

  • Competencia en SQL para consultas y manipulación de bases de datos.

  • Habilidad en integración y manejo de APIs.
  • Habilidad para hacer documentación técnica y guías de usuario.

  • Capacidad de desplegar y mantener aplicaciones.

Pros

  • Una oficina increíble que ocupa un piso entero (¡y ni te cuento la vista!).

  • Excelente equipo de trabajo.

  • Seguro complementario de salud.

  • Afiliación a Caja de Compensación.

  • KBank, posibilidad de obtener crédito 0% interés.

  • Plataforma de bienestar y salud Wellhub, con convenio a gimnasios.

  • KLearning, programa de educación continua.

  • Días libres en fechas importantes.

  • Frutas frescas todos los días y máquina de café a disposición.

  • Un mirador para descansar, sillas de masajes, etc.

  • Y muchísimas otras cosas que nos gustaría que puedas descubrir junto a nosotros

Required Skill Profession

Tecnología Eléctrica Y Energética


  • Job Details

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Unlock Your Machine Learning Potential: Insight & Career Growth Guide


Real-time Machine Learning Jobs Trends (Graphical Representation)

Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph here. Uncover the dynamic job market trends for Machine Learning in Chile, Chile, highlighting market share and opportunities for professionals in Machine Learning roles.

501 Jobs in Chile
501
29 Jobs in Chile
29
Download Machine Learning Jobs Trends in Chile and Chile

Are You Looking for Machine Learning Engineer (LLM Focus) Job?

Great news! is currently hiring and seeking a Machine Learning Engineer (LLM Focus) to join their team. Feel free to download the job details.

Wait no longer! Are you also interested in exploring similar jobs? Search now: .

The Work Culture

An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at KLog.co adheres to the cultural norms as outlined by Expertini.

The fundamental ethical values are:

1. Independence

2. Loyalty

3. Impartiapty

4. Integrity

5. Accountabipty

6. Respect for human rights

7. Obeying Chile laws and regulations

What Is the Average Salary Range for Machine Learning Engineer (LLM Focus) Positions?

The average salary range for a varies, but the pay scale is rated "Standard" in Chile. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.

What Are the Key Qualifications for Machine Learning Engineer (LLM Focus)?

Key qualifications for Machine Learning Engineer (LLM Focus) typically include Tecnología Eléctrica Y Energética and a list of qualifications and expertise as mentioned in the job specification. The generic skills are mostly outlined by the . Be sure to check the specific job listing for detailed requirements and qualifications.

How Can I Improve My Chances of Getting Hired for Machine Learning Engineer (LLM Focus)?

To improve your chances of getting hired for Machine Learning Engineer (LLM Focus), consider enhancing your skills. Check your CV/Résumé Score with our free Tool. We have an in-built Resume Scoring tool that gives you the matching score for each job based on your CV/Résumé once it is uploaded. This can help you align your CV/Résumé according to the job requirements and enhance your skills if needed.

Interview Tips for Machine Learning Engineer (LLM Focus) Job Success

KLog.co interview tips for Machine Learning Engineer (LLM Focus)

Here are some tips to help you prepare for and ace your Machine Learning Engineer (LLM Focus) job interview:

Before the Interview:

Research: Learn about the KLog.co's mission, values, products, and the specific job requirements and get further information about

Other Openings

Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.

Dress Professionally: Choose attire appropriate for the company culture.

Prepare Questions: Show your interest by having thoughtful questions for the interviewer.

Plan Your Commute: Allow ample time to arrive on time and avoid feeling rushed.

During the Interview:

Be Punctual: Arrive on time to demonstrate professionalism and respect.

Make a Great First Impression: Greet the interviewer with a handshake, smile, and eye contact.

Confidence and Enthusiasm: Project a positive attitude and show your genuine interest in the opportunity.

Answer Thoughtfully: Listen carefully, take a moment to formulate clear and concise responses. Highlight relevant skills and experiences using the STAR method.

Ask Prepared Questions: Demonstrate curiosity and engagement with the role and company.

Follow Up: Send a thank-you email to the interviewer within 24 hours.

Additional Tips:

Be Yourself: Let your personality shine through while maintaining professionalism.

Be Honest: Don't exaggerate your skills or experience.

Be Positive: Focus on your strengths and accomplishments.

Body Language: Maintain good posture, avoid fidgeting, and make eye contact.

Turn Off Phone: Avoid distractions during the interview.

Final Thought:

To prepare for your Machine Learning Engineer (LLM Focus) interview at KLog.co, research the company, understand the job requirements, and practice common interview questions.

Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the KLog.co's products or services and be prepared to discuss how you can contribute to their success.

By following these tips, you can increase your chances of making a positive impression and landing the job!

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