Lead design and improve recommender system pipelines and transformer-based customer sequence models. Build offline models, hyperparameter tuning, and online inference combining real-time session features. Oversee data gathering, preprocessing, deployment, data quality, and collaborate with MLOps to measure impact and success metrics.
Job Summary:
Understand the frameworks used currently in terms of recommender system pipelines
Come up with ways to improve the current algorithms and pipelines, responsible for the end-to-end testing of the algorithm along with collaborating with the MLOps team to see the model through
Dataset Gathering - Collect Data
Transformer Architecture - 1. Customer Sequence Modeling, 2. Multi Modal and Variable Length Inputs
Offline Model - 1. Build Offline Model, 2. Hyperparameter Tuning
Build Online Inference Path - 1. Combine Offline with real time session features
Data Quality - 1. Deployment, 2. Success Metric Improvement
Job Description: Proficiency in statistical analysis and machine learning using tools such as Python, R, and SQL is essential. Strong understanding of data modeling and data visualization techniques is required, along with experience in big data technologies like Hadoop and Spark. Knowledge of data wrangling and preprocessing is necessary. Strong analytical and problem-solving skills are crucial for developing insights and solutions from complex datasets. Expertise in predictive analytics and applied machine learning is also needed. The ability to measure impact and effectively communicate data-driven stories is important for influencing decision-making processes.
SKILLS:
– Proficiency in statistical analysis and machine learning (e.g., Python, R, SQL)
– Strong understanding of data modeling and data visualization techniques
– Experience with big data technologies (e.g., Hadoop, Spark)
– Knowledge of data wrangling and preprocessing
– Strong analytical and problem-solving skills
– Strong predictive analytics and applied machine learning skills
– Ability to measure impact and data story telling
• 10+ years experience
Understand the frameworks used currently in terms of recommender system pipelines
Come up with ways to improve the current algorithms and pipelines, responsible for the end-to-end testing of the algorithm along with collaborating with the MLOps team to see the model through
Dataset Gathering - Collect Data
Transformer Architecture - 1. Customer Sequence Modeling, 2. Multi Modal and Variable Length Inputs
Offline Model - 1. Build Offline Model, 2. Hyperparameter Tuning
Build Online Inference Path - 1. Combine Offline with real time session features
Data Quality - 1. Deployment, 2. Success Metric Improvement
Job Description: Proficiency in statistical analysis and machine learning using tools such as Python, R, and SQL is essential. Strong understanding of data modeling and data visualization techniques is required, along with experience in big data technologies like Hadoop and Spark. Knowledge of data wrangling and preprocessing is necessary. Strong analytical and problem-solving skills are crucial for developing insights and solutions from complex datasets. Expertise in predictive analytics and applied machine learning is also needed. The ability to measure impact and effectively communicate data-driven stories is important for influencing decision-making processes.
SKILLS:
– Proficiency in statistical analysis and machine learning (e.g., Python, R, SQL)
– Strong understanding of data modeling and data visualization techniques
– Experience with big data technologies (e.g., Hadoop, Spark)
– Knowledge of data wrangling and preprocessing
– Strong analytical and problem-solving skills
– Strong predictive analytics and applied machine learning skills
– Ability to measure impact and data story telling
• 10+ years experience
Top Skills
Hadoop
Mlops
Python
R
Recommender Systems
Spark
SQL
Transformer
Similar Jobs
Artificial Intelligence • Machine Learning • Generative AI
The Data Scientist will shape and analyze the infrastructure that powers OpenAI's products, developing metrics, forecasting models, and dashboards to enhance resource usage and performance efficiency.
Top Skills:
PythonSQL
.png)
eCommerce • Fintech • Hardware • Payments • Software • Financial Services
Outbound-focused Account Executive selling Square ecosystem to restaurant SMBs. Source and prospect new logos, run discovery, demos, negotiate and close deals, manage full sales cycle, and use Salesforce to track pipeline while meeting monthly quotas.
Top Skills:
Salesforce,Square,Afterpay
eCommerce • Fintech • Hardware • Payments • Software • Financial Services
Lead and scale outbound pipeline generation by managing BDRs, defining outbound strategy, improving messaging and sequencing, driving SQL/meeting targets, forecasting, and cross-functional alignment to deliver high-quality top-of-funnel pipeline.
Top Skills:
Salesforce,Outreach
What you need to know about the Los Angeles Tech Scene
Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.
Key Facts About Los Angeles Tech
- Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
- Key Industries: Artificial intelligence, adtech, media, software, game development
- Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
- Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering
