Senior Machine Learning Engineer - 1665

aKube; Santa Monica (CA); Híbrido; USD 118.000 - 168.000; Jornada completa

Descripción de la vacante

aKube in Santa Monica, CA is seeking a seasoned ML/NLP Engineer to design, develop, and deploy content classification and segmentation models in production. The role emphasizes multi-class and multi-label classification, feature engineering, and scalable workflows in Python, SQL, Spark, and ML frameworks.

You will collaborate with data scientists and software engineers, contribute to model evaluation, and maintain clean, tested code.

Formación

• 5+ years hands-on industry experience deploying ML models in production.
• Proficient Python programming with pandas and scikit-learn.
• Hands-on supervised ML, especially classification models.
• NLP experience including text-based feature development.
• Strong feature engineering, preprocessing, and model evaluation skills.
• Strong SQL for querying and analyzing large datasets.

Responsabilidades

• Design, develop, and improve ML models for content classification and segmentation.
• Build classification models to assign content categories, genres, and segments.
• Enhance existing models and expand coverage across content types.
• Develop multi-class and multi-label classifiers using supervised learning.
• Perform EDA, feature engineering, model training, tuning, and evaluation.
• Process structured and semi-structured data with Python, pandas, SQL, and Spark.
• Develop text-based and metadata-driven features to improve accuracy.
• Apply categorical encoding, normalization, feature selection, and hyperparameter tuning.
• Build scalable ML workflows to support production apps.
• Collaborate with data scientists, software engineers, and stakeholders to implement ML solutions.
• Maintain clean, modular, tested, and documented ML code.

Conocimientos

Python

Pandas

Scikit-learn

Machine Learning

NLP

Feature engineering

SQL

Spark

Multi-class classification

Text features

Git

Educación

Bachelor's degree in CS/DS/Statistics/Engineering or related field

Herramientas

Git

Spark

Airflow

Luigi

AWS

Descripción del empleo

Santa Monica, United States | Posted on 10/21/2026

Onsite / Hybrid / Remote: Hybrid. Onsite Monday through Thursday. Remote Friday.

Duration: 18 months

Rate Range: Up to $103.50/hr on w2

Work Authorization:GC, USC, All valid EADs except OPT, CPT, H1B

Must Have:

• 5+ years of hands‑on industry experience developing and deploying machine learning models in production.
  


• Strong Python programming skills, including pandas and scikit‑learn.
  


• Hands‑on experience with supervised machine learning, particularly classification models.
  


• Experience with Natural Language Processing (NLP), including text‑based feature development.
  


• Strong experience with feature engineering, preprocessing, and model evaluation.
  


• Strong SQL skills for querying and analyzing large datasets.
  

Responsibilities

• Design, develop, and improve machine learning models for content classification and segmentation.
  


• Build classification models that automatically assign content categories, genres, and segments.
  


• Enhance existing machine learning models and expand classification coverage across different content types.
  


• Develop multi‑class and multi‑label classification models using supervised learning techniques.
  


• Perform exploratory data analysis, feature engineering, model training, tuning, and evaluation.
  


• Process structured and semi‑structured datasets using Python, pandas, SQL, and Spark.
  


• Develop text‑based and metadata‑driven features to improve classification accuracy.
  


• Apply techniques such as categorical encoding, normalization, feature selection, and hyperparameter optimization.
  


• Build scalable machine learning workflows to support production applications.
  


• Collaborate with data scientists, software engineers, and business stakeholders to implement ML solutions.
  


• Maintain clean, modular, tested, and documented machine learning code.
  

Qualifications

• Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field, or equivalent practical experience.
  


• Minimum 5 years of relevant machine learning experience, with substantial hands‑on model development.
  


• Strong understanding of classification algorithms, including logistic regression, decision trees, random forests, ensemble methods, and gradient‑boosted models.
  


• Experience building, training, evaluating, and deploying machine learning classifiers.
  


• Experience with multi‑class and/or multi‑label classification.
  


• Experience with NLP techniques and text‑derived features.
  


• Strong knowledge of cross‑validation, model performance metrics, and hyperparameter tuning.
  


• Ability to independently deliver machine learning solutions from initial data exploration through production implementation.
  


• Experience with software development practices, including Git, testing, logging, and code reviews.
  

Nice to Have

• Master's degree in Computer Science, Machine Learning, Statistics, Mathematics, or a related field.
  


• Experience in media, entertainment, streaming, or digital content platforms.
  


• Experience building classifiers using content metadata, catalog data, or high‑dimensional datasets.
  


• Experience with NLP techniques such as TF‑IDF, text embeddings, and semantic representations.
  


• Experience with workflow orchestration tools such as Airflow or Luigi.
  


• Experience with AWS or similar cloud environments.
  


• Experience with search, recommendation systems, or content categorization.