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Senior Machine Learning Engineer

extra parental leave - work from anywhere - fully flexible
Remote: 
Full Remote
Contract: 
Salary: 
160 - 192K yearly
Experience: 
Mid-level (2-5 years)
Work from: 

Offer summary

Qualifications:

3+ years of experience in software systems, Background in MLOps, engineering or data science, Experience with ML frameworks (TensorFlow, PyTorch), Proficiency in deep learning deployment systems, Cloud platform experience (AWS preferred).

Key responsabilities:

  • Develop feature engineering strategies for ML models
  • Design robust systems for model inference
  • Build and maintain machine learning lifecycle infrastructure
  • Collaborate with cross-functional teams in a fast-paced environment
  • Own initiatives from conception to deployment
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Socure Scaleup https://www.socure.com/
501 - 1000 Employees
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Job description

Predictive analytics and machine learning power Socure’s groundbreaking technology and fuel our mission to verify 100% of good identities in real time and completely eliminate identity fraud on the internet.

Socure is the world leader in digital identity verification and fraud prevention. Our recent awards include Forbes 2022 America’s Best Startup Employers, The Forbes Cloud 100, The Deloitte Technology Fast 500, and Inc. 5000’s fastest growing companies.

Listen to why some of the world’s top technology investors see the enormous, transformative potential in Socure’s mission and products:

https://www.youtube.com/watch?v=ifM9_jPQCv8

Overview

We are seeking a Senior Machine Learning Engineer to join our US-based Machine Learning (ML) Platform team. Our team is dedicated to designing, building, and maintaining scalable infrastructure and tools that empower machine learning and deep learning projects at Socure. As a key member of the ML Platform team, you will play a crucial role in the end-to-end ML lifecycle, from data collection and analysis to the development, deployment, and optimization of robust ML pipelines. If you have a passion for building efficient, reliable infrastructure and developing tools that simplify and enhance the work of data scientists and ML engineers, we’d love to connect and discuss your background and experiences.


 

Role and Responsibilities
  • Develop feature engineering strategies and solutions to support machine learning models

  • Design and implement robust and scalable systems for efficient model inference

  • Build and maintain infrastructure supporting feature engineering, model serving, Gen-AI agents, and related components across the machine learning lifecycle

  • Contribute to the development and enhancement of a comprehensive feature platform to streamline and optimize feature creation and management

  • Demonstrate best practices in version control and continuous integration / delivery

  • Own and drive initiatives from conception to deployment and monitoring

  • Collaborate with data scientists, engineers, product managers, and other key stakeholders in a fast-paced cross-functional environment

Required Qualifications 
  • 3+ years of experience building and maintaining production-quality software systems

  • Background in software engineering, data engineering, MLOps, data science, or research

  • Experience with popular ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)

  • Experience with containerization (e.g., Docker) and/or container-orchestration systems (e.g., Kubernetes, Argo CD)

  • Proficiency in deep learning/machine learning deployment and inference systems

  • Familiarity with ML engineering best practices and readiness to work in a fast-paced, dynamic environment

  • Experience with databases and/or data warehouses (e.g., DynamoDB, Snowflake or Redshift)

  • Experience with distributed data processing and streaming frameworks (e.g., Apache Spark, Apache Kafka)

  • Experience with workflow orchestration tools (e.g., Apache Airflow)

  • Ability to develop user-centric solutions and effectively translate stakeholder needs into technical requirements

  • Experience with cloud platforms (experience with AWS and/or Terraform is a plus)

Preferred Qualifications
  • Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field

  • Experience with advanced feature engineering and feature store platforms

  • Knowledge of security best practices in ML deployment and data handling

  • Experience with CI/CD pipelines specifically tailored for ML applications

  • Proficiency in optimizing  for latency, scalability, and high availability in production environments

  • Strong design skills for developing effective and efficient ML systems

  • Hands-on experience with monitoring and observability tools for ML systems (e.g., Prometheus, Grafana)

  • Strong communication skills for collaborating with non-technical stakeholders

  • Ability to contribute to and foster a positive team culture
     

    Salary Disclosure:
    Base Salary range: $160,000 - $190,000

    This represents the expected salary range for this job requisition. Final offers may vary from the amount listed based on factors including geography, candidate experience and expertise, and other job related factors. Socure's compensation and rewards package for full time roles includes a market competitive salary, equity,  comprehensive benefits, and, for applicable roles, commissions plans or an annual discretionary performance bonus. 

    Socure is all about encouraging people to push the boundaries of what’s possible through top-tier performance, innovation, ownership, and shared expertise.

Socure is all about encouraging people to push the boundaries of what’s possible through top-tier performance, innovation, ownership, and shared expertise.

We empower excellence by providing great perks and benefits to both our fully remote employees in North America and our hybrid teams in India.

To learn more, check out Socure’s Career Page: https://www.socure.com/company/careers

Socure is an equal opportunity employer and value diversity of all kinds at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

To learn more about how our work is changing the world, check out these articles and videos:

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Experience

Level of experience: Mid-level (2-5 years)
Industry :
Internet
Spoken language(s):
English
Check out the description to know which languages are mandatory.

Other Skills

  • Collaboration
  • Team Leadership
  • Verbal Communication Skills

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