Senior Machine Learning Engineer

Valid8 Financial, Inc.; Fremont (CA); Hybrid; USD 100,000 - 140,000; Full time

Job summary

An innovative company is on the lookout for a hands-on Machine Learning Engineer to enhance their ML infrastructure and deployment processes. This role involves collaborating with data scientists to streamline the ML lifecycle, from data ingestion to model monitoring. You'll be instrumental in building robust CI/CD pipelines and deploying models using cutting-edge tools like Databricks and AWS services. Join a forward-thinking organization where your contributions will significantly impact the efficiency and effectiveness of machine learning operations. If you are passionate about MLOps and thrive in a dynamic environment, this opportunity is perfect for you.

Qualifications

• 3+ years of experience in MLOps required.
• Strong proficiency in Databricks and PySpark.
• Hands-on with AWS services essential.

Responsibilities

• Deploy ML models and build CI/CD pipelines.
• Architect and manage ML infrastructure on AWS.
• Implement monitoring systems for model performance.

Skills

MLOps

AWS

Databricks

PySpark

CI/CD Pipelines

Model Deployment

Education

Degree in Computer Science

Tools

GitHub Actions

GitLab CI

Jenkins

Airflow

Prefect

MLflow

SageMaker

Amazon Redshift

Job description

We’re seeking a hands-on Machine Learning Engineer (MLOps / ML Infrastructure Engineer who blends the best of DevOps, Data Engineering, and Machine Learning Engineering). Your mission will be to deploy ML models, build robust CI/CD pipelines, and maintain a scalable data and ML infrastructure leveraging AWS, Databricks, and Amazon Redshift.

You’ll work closely with data scientists to streamline the entire ML lifecycle—from data ingestion and model training to deployment and monitoring in production.

• Model Deployment: Design and implement scalable deployment workflows for machine learning models using tools like MLflow, SageMaker, or Databricks ML.
• CI/CD Automation: Build and maintain end-to-end CI/CD pipelines for model training, validation, and deployment using tools such as GitHub Actions, GitLab CI, or Jenkins.
• Cloud Infrastructure: Architect and manage ML infrastructure on AWS, including EC2, S3, Lambda, EKS, SageMaker, and Redshift.
• Databricks Operations: Maintain Databricks workspaces, develop PySpark jobs, manage clusters, and integrate ML workloads with data pipelines.
• Data Pipelines: Build robust data ingestion and transformation pipelines from Redshift and other sources to serve model training and inference workflows.
• Monitoring & Observability: Implement systems for tracking model performance, data drift, and pipeline health using CloudWatch, Databricks metrics, or custom dashboards.
• Automation & Orchestration: Use tools like Airflow, Prefect, or Databricks Jobs to automate workflows for training and batch inference.
• Data Governance: Ensure data workflows and ML pipelines adhere to governance, lineage, access control, and compliance policies across environments.

Minimum Qualifications

• 3+ years of experience in MLOps
• Degree in Computer Science, or Engineering discipline required
• Strong proficiency in Databricks and PySpark
• Hands-on with AWS services (S3, Redshift, Lambda, SageMaker, IAM, CloudFormation/Terraform)
• Proven experience with AI model deployment pipelines in production environments
• Solid experience in building CI/CD pipelines
• Travel 10%

Hybrid Workplace

SoundThinking follows a hybrid schedule for employees who live equal to or less than 50 miles from one of our office locations, which include Fremont, CA, Tucson, AZ, Washington, D.C., or Iselin, NJ. Employees are expected to work onsite 3 days per week – the specific days are dependent on the office location.

SoundThinking provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, SoundThinking complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

SoundThinking expressly prohibits any form of workplace harassment based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. Improper interference with the ability of SoundThinking’s employees to perform their job duties may result in discipline up to and including discharge. If you are an individual with a disability and require a reasonable accommodation to complete any part of the application process, or are limited in the ability or unable to access or use this online application process and need an alternative method for applying, you may contact SoundThinking at [e-mail] for assistance.

The above salary range is based on a good faith estimate made at the time of publication and may be modified in the future. The pay offered to a candidate may vary within this range depending on factors such as education, experience, and geographic location

Note: The Company reserves exclusive right in its sole discretion to modify, adjust, delete, add or otherwise change the above at any time.

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