DescriptionWe have an exciting and rewarding opportunity for you to take your software engineering career to the next level. We are building a next generation AI-driven Surveillance platform that detects regulatory violations insider risk misconduct and behavioral anomalies across enterprise communications and collaboration systems.
As a Senior MLE on the team you will design build and productionize ML and LLM powered detection systems that operate at scale across high-volume communication streams. You will work at the intersection of Risk modeling NLP and transformer architectures near real-time inference systems regulatory explainability and auditability. This is a hands-on senior role requiring deep expertise in applied NLP LLM integration scalable ML systems and production grade engineering discipline. This role offers a chance to collaborate with product managers architects data science and operational teams while also engaging in software engineering communities to explore new and emerging technologies.
Job responsibilities
- Design LLM powered features such as risk detection alert explanation conversation summarization reviewer assisted co-pilots
- Implement explainability techniques (SHAP LIME attention visualization) ensuring model outputs are traceable versioned and reproducible
- Optimize inference latency and token efficiency for production environments
- Implement RAG and LLM based risk analysis pipelines processing data at web scale
- Bake in augmentation mechanisms leveraging legacy regular expressions for filtering and optimization
- Design real-time and batch processing and scoring pipelines (kafka/spark)
- Implement experiment tracking model versioning and CI/CD for ML
- Conduct monitoring to detect and alert drift bias and performance degradation
- Work closely within a cross-functional team following agile based processes
- Collaborate closely with Product Managers SRE and Compliance SMEs to continuously improve product adoption reliability and outcomes
Required qualifications capabilities and skills
- 8 years experience in cloud based applications with 4 years of experience as an MLE
- Strong foundation in Information Retrieval Natural Language Processing and
- Expert in functional programming and JVM based languages- Python/Kotlin Java
- Experience integrating models into cloud scale microservices based architectures
- Experience with one or more ML frameworks - Pytorch Tensorflow SciKit NeMo Huggingface Transformers
- Hands-on experience with AWS services such as SageMaker ECS Lambda functions Bedrock
- Experience/Exposure to SQL NoSQL and messaging stacks
- Excellent verbal & written communication skills and bias for action and ownership in early stage env
- Operational experience in supporting an enterprise grade ML application in production
Preferred qualifications capabilities and skills
- Knowledge of Databricks is nice to have
- Experience with any of the MLOps frameworks such MLflow Kubeflow
- Experience in surveillance fraud detection fintech or risk systems is a strong plus
Required Experience:
Senior IC
DescriptionWe have an exciting and rewarding opportunity for you to take your software engineering career to the next level. We are building a next generation AI-driven Surveillance platform that detects regulatory violations insider risk misconduct and behavioral anomalies across enterprise communi...
DescriptionWe have an exciting and rewarding opportunity for you to take your software engineering career to the next level. We are building a next generation AI-driven Surveillance platform that detects regulatory violations insider risk misconduct and behavioral anomalies across enterprise communications and collaboration systems.
As a Senior MLE on the team you will design build and productionize ML and LLM powered detection systems that operate at scale across high-volume communication streams. You will work at the intersection of Risk modeling NLP and transformer architectures near real-time inference systems regulatory explainability and auditability. This is a hands-on senior role requiring deep expertise in applied NLP LLM integration scalable ML systems and production grade engineering discipline. This role offers a chance to collaborate with product managers architects data science and operational teams while also engaging in software engineering communities to explore new and emerging technologies.
Job responsibilities
- Design LLM powered features such as risk detection alert explanation conversation summarization reviewer assisted co-pilots
- Implement explainability techniques (SHAP LIME attention visualization) ensuring model outputs are traceable versioned and reproducible
- Optimize inference latency and token efficiency for production environments
- Implement RAG and LLM based risk analysis pipelines processing data at web scale
- Bake in augmentation mechanisms leveraging legacy regular expressions for filtering and optimization
- Design real-time and batch processing and scoring pipelines (kafka/spark)
- Implement experiment tracking model versioning and CI/CD for ML
- Conduct monitoring to detect and alert drift bias and performance degradation
- Work closely within a cross-functional team following agile based processes
- Collaborate closely with Product Managers SRE and Compliance SMEs to continuously improve product adoption reliability and outcomes
Required qualifications capabilities and skills
- 8 years experience in cloud based applications with 4 years of experience as an MLE
- Strong foundation in Information Retrieval Natural Language Processing and
- Expert in functional programming and JVM based languages- Python/Kotlin Java
- Experience integrating models into cloud scale microservices based architectures
- Experience with one or more ML frameworks - Pytorch Tensorflow SciKit NeMo Huggingface Transformers
- Hands-on experience with AWS services such as SageMaker ECS Lambda functions Bedrock
- Experience/Exposure to SQL NoSQL and messaging stacks
- Excellent verbal & written communication skills and bias for action and ownership in early stage env
- Operational experience in supporting an enterprise grade ML application in production
Preferred qualifications capabilities and skills
- Knowledge of Databricks is nice to have
- Experience with any of the MLOps frameworks such MLflow Kubeflow
- Experience in surveillance fraud detection fintech or risk systems is a strong plus
Required Experience:
Senior IC
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