Netflix is seeking a highly skilled and intellectually curious Machine Learning Engineer (NLP + Quant Trading Models) to join our advanced data science and AI team. This remote, full-time position offers a unique opportunity to work at the intersection of natural language processing (NLP), financial modeling, and quantitative trading strategies, helping Netflix optimize business and content investment decisions using next-generation AI technologies.
In this role, you will design and deploy scalable machine learning models that leverage text analytics, predictive modeling, and algorithmic trading frameworks. You’ll collaborate with cross-functional teams including data scientists, quantitative researchers, engineers, and finance analysts to create intelligent systems that can identify opportunities, predict market trends, and enhance strategic decision-making through data-driven insights.
If you have deep expertise in machine learning, NLP, and quantitative modeling — and thrive in an environment that values creativity, innovation, and high performance — this role is designed for you.
Key Responsibilities:
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Design, train, and deploy machine learning models for NLP-based data analysis and quantitative financial forecasting.
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Develop algorithms for automated pattern recognition, sentiment analysis, and financial time-series modeling.
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Integrate AI-driven predictive systems into Netflix’s decision-making and content investment processes.
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Build scalable pipelines for data collection, cleaning, and feature engineering across structured and unstructured data sources.
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Collaborate closely with data scientists, engineers, and product stakeholders to define model objectives and evaluate performance metrics.
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Experiment with transformer-based architectures (e.g., BERT, GPT, LLaMA) and other deep learning frameworks to enhance language understanding capabilities.
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Utilize advanced quantitative trading techniques and statistical models to simulate performance and forecast ROI.
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Continuously monitor, evaluate, and refine model performance for accuracy, scalability, and fairness.
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Document models, algorithms, and methodologies for reproducibility and transparency.
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Stay current with the latest advancements in AI, deep learning, and quant modeling to integrate best practices into Netflix’s AI ecosystem.
Required Skills and Qualifications:
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Master’s or Ph.D. in Computer Science, Machine Learning, Data Science, Applied Mathematics, or Quantitative Finance.
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4+ years of hands-on experience in machine learning, NLP, or quantitative modeling.
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Strong proficiency in Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn, Hugging Face Transformers, and NumPy.
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Proven experience building and deploying NLP models (language modeling, sentiment analysis, topic modeling, summarization, etc.).
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Solid understanding of quantitative trading models, statistical arbitrage, and time-series forecasting.
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Experience working with large-scale data processing tools (e.g., Spark, Databricks, or Kafka).
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Strong mathematical foundation in probability, statistics, and optimization.
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Familiarity with cloud-based ML platforms (AWS SageMaker, GCP Vertex AI, or Azure ML).
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Excellent problem-solving skills, attention to detail, and an analytical mindset.
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Effective communication and collaboration skills in a distributed remote environment.
Experience:
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Minimum 4–7 years of professional experience in machine learning, quantitative research, or applied AI.
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Prior experience in financial analytics, algorithmic trading, or investment modeling is highly preferred.
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Proven record of deploying end-to-end ML systems from data ingestion to model deployment and monitoring.
Working Hours:
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Full-Time, Remote (USA)
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Standard work schedule: Monday to Friday, flexible hours across U.S. time zones.
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Occasional collaboration meetings with global teams may require flexible scheduling.
Knowledge, Skills, and Abilities:
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Deep understanding of NLP concepts, deep learning architectures, and quantitative finance principles.
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Proficiency in data visualization tools (e.g., Plotly, Tableau, or Power BI) for communicating results.
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Strong ability to translate complex analytical findings into actionable business insights.
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Familiarity with MLOps best practices, version control (Git), and CI/CD pipelines.
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High adaptability to emerging AI trends, especially in multimodal learning and reinforcement learning.
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A growth mindset with a passion for continuous learning and experimentation.
Benefits:
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Competitive compensation and performance-based bonuses.
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Comprehensive health, dental, and vision insurance coverage.
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401(k) with company match and financial wellness programs.
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Unlimited paid time off (PTO) and flexible work hours.
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Remote-first culture with opportunities to collaborate across global teams.
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Annual learning and development stipend for certifications or advanced training.
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Access to state-of-the-art computing infrastructure and AI tools.
Why Join Netflix:
At Netflix, we are redefining what’s possible with technology. As part of our AI and machine learning team, you’ll contribute to world-class innovations that power smarter decision-making, enhance customer experiences, and shape the future of streaming intelligence. We value creativity, autonomy, and curiosity — and we empower our engineers to explore bold ideas that make a measurable impact.
Joining Netflix means being part of a culture that encourages experimentation, embraces data, and rewards excellence. You’ll have the opportunity to work with some of the brightest minds in AI and finance while developing solutions that blend science, art, and strategy.
How to Apply:
If you’re an ambitious machine learning engineer who loves solving complex problems at scale, we’d love to hear from you.
📧 Submit your application by sending your resume, GitHub/portfolio links, and a brief statement of interest to:
careers@netflix.com
Please include “Application for Machine Learning Engineer – NLP + Quant Trading Models (Remote)” in the subject line.