ML Engineer Hybrid in San Francisco CA
Holistic Partners, Inc
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San Francisco, CA
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Mid-Senior level
Posted March 14, 2026
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Responsibilities
Commitments
Responsibilities
- Strong expertise with data handling and data analysis, feature engineering
- Creating the necessary infrastructure and tools for training, deploying, and monitoring machine learning models
- Ability to turn prototypes to production Must have:
- Strong working experience in python including Pandas, numpy and FastAPI/Flask frameworks.
- Good knowledge of cloud services, preferably AWS.
- Strong Database knowledge and be able to write and comprehend SQL queries.
- Experience building API, Calculation Engines, batch, and real time modules supporting web applications used by Trading or Portfolio management teams
- Experience building real time applications for Structured, Rates, Corporate or Municipal Fixed Income Desk Experience with Python programming, AWS Stack - EKS, API Gateway, Lamda, Redis.
- Databases Postgress, S3 technologies, Integrating with market data providers like Bloomberg, TradeWeb etc.
- Should have worked on any ETL pipeline
- 10-12 years of Experience in Asset management or financial services industry
- Strong communication skills, capable to coordinate with various stakeholders Nice to have:
Commitments
Job Title: ML Engineer Location: SFO, CA (Hybrid.
3 days onsite, 2 days remote) Duration: 6+ Months Interview Process: Video
Ability to turn prototypes to production Must have:
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Requirements
- 3 days onsite, 2 days remote) Duration: 6+ Months Interview Process: Video
- Strong programming skills in languages like Python, Java, and potentially others used in machine learning
- Knowledge of ML Algorithms and Techniques
- Experience with ML frameworks and libraries such as TensorFlow, PyTorch, and libraries like scikit-learn
- Strong expertise with data handling and data analysis, feature engineering
- Creating the necessary infrastructure and tools for training, deploying, and monitoring machine learning models
- Ability to turn prototypes to production Must have:
- Strong working experience in python including Pandas, numpy and FastAPI/Flask frameworks.
- Good knowledge of cloud services, preferably AWS.
- Strong Database knowledge and be able to write and comprehend SQL queries.
- Should have Graphql knowledge
- Experience building API, Calculation Engines, batch, and real time modules supporting web applications used by Trading or Portfolio management teams
- Experience building real time applications for Structured, Rates, Corporate or Municipal Fixed Income Desk Experience with Python programming, AWS Stack - EKS, API Gateway, Lamda, Redis.
- Databases Postgress, S3 technologies, Integrating with market data providers like Bloomberg, TradeWeb etc.
- Should have worked on any ETL pipeline
- 10-12 years of Experience in Asset management or financial services industry
- Strong communication skills, capable to coordinate with various stakeholders Nice to have:
- Knowledge of JupyterLab (Good to have)
- Knowledge of Apache Airflow or any Workflow management tool (Good to have)
- Strong learning mindset to learn and perform POC on new advanced technologies and services related to Data Science platforms.
- Experience working on Financial Services Equity or Fixed Income trading use cases
Preferred Skills
- Good knowledge of cloud services, preferably AWS.
- Should have Graphql knowledge
- Experience building API, Calculation Engines, batch, and real time modules supporting web applications used by Trading or Portfolio management teams
- Should have worked on any ETL pipeline
- Knowledge of JupyterLab (Good to have)
- Knowledge of Apache Airflow or any Workflow management tool (Good to have)
- Knowledge of DevOps is plus and good to have.
- Strong learning mindset to learn and perform POC on new advanced technologies and services related to Data Science platforms.
- Experience working on Financial Services Equity or Fixed Income trading use cases
Job Title: ML Engineer Location: SFO, CA (Hybrid. 3 days onsite, 2 days remote) Duration: 6+ Months Interview Process: Video
Strong programming skills in languages like Python, Java, and potentially others used in machine learning
Knowledge of ML Algorithms and Techniques
Experience with ML frameworks and libraries such as TensorFlow, PyTorch, and libraries like scikit-learn
Strong expertise with data handling and data analysis, feature engineering
Creating the necessary infrastructure and tools for training, deploying, and monitoring machine learning models
Ability to turn prototypes to production Must have:
Strong working experience in python including Pandas, numpy and FastAPI/Flask frameworks.
Good knowledge of cloud services, preferably AWS.
Strong Database knowledge and be able to write and comprehend SQL queries.
Should have Graphql knowledge
Experience building API, Calculation Engines, batch, and real time modules supporting web applications used by Trading or Portfolio management teams
Experience building real time applications for Structured, Rates, Corporate or Municipal Fixed Income Desk Experience with Python programming, AWS Stack - EKS, API Gateway, Lamda, Redis. Databases Postgress, S3 technologies, Integrating with market data providers like Bloomberg, TradeWeb etc.
Should have worked on any ETL pipeline
10-12 years of Experience in Asset management or financial services industry
Strong communication skills, capable to coordinate with various stakeholders Nice to have:
Knowledge of JupyterLab (Good to have)
Knowledge of Apache Airflow or any Workflow management tool (Good to have)
Knowledge of DevOps is plus and good to have.
Strong learning mindset to learn and perform POC on new advanced technologies and services related to Data Science platforms.
Experience working on Financial Services Equity or Fixed Income trading use cases
Strong programming skills in languages like Python, Java, and potentially others used in machine learning
Knowledge of ML Algorithms and Techniques
Experience with ML frameworks and libraries such as TensorFlow, PyTorch, and libraries like scikit-learn
Strong expertise with data handling and data analysis, feature engineering
Creating the necessary infrastructure and tools for training, deploying, and monitoring machine learning models
Ability to turn prototypes to production Must have:
Strong working experience in python including Pandas, numpy and FastAPI/Flask frameworks.
Good knowledge of cloud services, preferably AWS.
Strong Database knowledge and be able to write and comprehend SQL queries.
Should have Graphql knowledge
Experience building API, Calculation Engines, batch, and real time modules supporting web applications used by Trading or Portfolio management teams
Experience building real time applications for Structured, Rates, Corporate or Municipal Fixed Income Desk Experience with Python programming, AWS Stack - EKS, API Gateway, Lamda, Redis. Databases Postgress, S3 technologies, Integrating with market data providers like Bloomberg, TradeWeb etc.
Should have worked on any ETL pipeline
10-12 years of Experience in Asset management or financial services industry
Strong communication skills, capable to coordinate with various stakeholders Nice to have:
Knowledge of JupyterLab (Good to have)
Knowledge of Apache Airflow or any Workflow management tool (Good to have)
Knowledge of DevOps is plus and good to have.
Strong learning mindset to learn and perform POC on new advanced technologies and services related to Data Science platforms.
Experience working on Financial Services Equity or Fixed Income trading use cases