Machine Learning Engineer II (Remote)

NLP PEOPLE; Barcelona; A distancia; EUR 40.000 - 80.000; Jornada completa

Descripción de la vacante

An innovative firm is seeking a Machine Learning Engineer II to join a dynamic product team dedicated to crafting cutting-edge software solutions that delight users. In this collaborative role, you'll design and implement AI/ML algorithms, ensuring that business needs are met through effective machine learning solutions. You'll engage with diverse teams, from UX to engineering, and contribute to the entire product lifecycle. This position offers a unique opportunity to enhance your skills in a supportive environment while making a significant impact on product development. If you're passionate about machine learning and eager to drive innovation, this role is perfect for you.

Formación

• 1-3 years of relevant experience in ML development and ops lifecycle.
• Expertise in modern scripting languages, preferably Python.
• Familiarity with data analysis tools and cloud platforms.

Responsabilidades

• Collaborate with product teams to create scalable ML solutions.
• Monitor production systems and ensure performance objectives are met.
• Participate in learning activities around modern software design.

Conocimientos

Machine Learning Development

Python

Data Engineering

SQL

Statistical Analysis

Collaboration

Educación

High School Diploma or GED

Bachelor's Degree (Preferred)

Herramientas

Jupyter Notebooks

Pandas

TensorFlow

PyTorch

BigQuery

Node.js

Descripción del empleo

The Machine Learning Engineer II is responsible for joining a product team and contributing to the software design, algorithm design, and overall product lifecycle for a product that our users love. The engineering process is highly collaborative. ML Engineers are expected to pair daily as they work through user stories and support products as they evolve.

ML Engineers may be involved in designing and implementing AI / ML algorithms to embed directly into software products. Activities may include using specific HD process techniques, integration, design, and development. The role could interface with Business Stakeholders, Technology Infrastructure teams, and Development teams to ensure that business requirements are properly met within a machine learning solution. The role may also be involved in performance tuning, testing, and product monitoring. Other responsibilities may include performing customer outreach, designing ML educational material, and data engineering.

ML Engineers should be able to operate independently with minimum guidance from others, although will typically work as part of a team with varying skill levels to create, support, and deploy production applications. This role will review submitted code and provide feedback to improve, based on best practices.

Key Responsibilities :

• 65% Delivery and Execution : Collaborates and pairs with other product team members (UX, engineering, and product management) to create secure, reliable, scalable machine learning solutions; Documents, reviews, and ensures that all quality and change control standards are met; Works with Product Team to ensure user stories that are developer-ready, easy to understand, and testable; Writes custom code or scripts to automate infrastructure, monitoring services, and test cases; Writes custom code or scripts to do “destructive testing” to ensure adequate resiliency in production; Program configuration / modification and setup activities on large projects using HD approved methodology; Configures commercial off the shelf solutions to align with evolving business needs; Creates meaningful dashboards, logging, alerting, and responses to ensure that issues are captured and addressed proactively.
• 15% Learning : Participates in learning activities around modern software design, machine learning, and development core practices (communities of practice); Proactively views articles, tutorials, and videos to learn about new technologies and best practices being used within other technology organizations.
• 20% Support and Enablement : Fields questions from other product teams or support teams; Monitors tools and participates in conversations to encourage collaboration across product teams; Provides application support for software running in production; Proactively monitors production Service Level Objectives for products; Proactively reviews the Performance and Capacity of all aspects of production : code, infrastructure, data, message processing, and prediction quality.

Direct Manager / Direct Reports :

• This Position typically reports to Software Engineer Manager or Sr Software Engineer Manager.
• This Position has 0 Direct Reports.

Travel Requirements :

Typically requires overnight travel 5% to 20% of the time.

Physical Requirements :

Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.

Working Conditions :

Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.

Minimum Qualifications :

• Must be eighteen years of age or older.
• Must be legally permitted to work in the United States.

Preferred Qualifications :

• 1 – 3 years of relevant work experience.
• Expertise in ML development and ML ops lifecycle.
• Experience working with multiple leading ML models.
• Experience in a modern scripting language (preferably Python).
• Experience in effective data engineering practices and big data platforms such as BigQuery, Data Store, etc.
• Experience in modern web application framework such as Node.js.
• Experience in writing SQL queries against a relational database.
• Familiarity with algorithms such as clustering, forecasting, anomaly detection, and neural networks.
• Familiarity with basic statistics and regression algorithms.
• Familiarity with Data Analysis and Machine Learning Tools and Libraries like Jupyter Notebooks, Pandas, SciPy, Scikit-learn, Gensim, tensorflow, pytorch, etc.
• Familiarity with Google Cloud Platform and AI / ML related components such as Vertex AI, BigQueryML, and AutoML.
• Familiarity with a Linux or Unix based environment.
• Familiarity with a CI / CD toolchain.
• Familiarity with REST and effective web service design.
• Familiarity with production systems design including High Availability, Disaster Recovery, Performance, Efficiency, and Security.

The knowledge, skills and abilities typically acquired through the completion of a high school diploma and / or GED.