Associate Machine Learning Engineer - #1412320
Socure
Date: 6 hours ago
City: Carson City, NV
Salary:
$115,000
-
$140,000
per year
Contract type: Full time
Remote

At Socure, we’re on a mission—to verify 100% of good identities in real time and eliminate identity fraud from the internet.
Using predictive analytics and advanced machine learning trained on billions of signals to power RiskOS, Socure has created the most accurate identity verification and fraud prevention platform in the world. Trusted by thousands of leading organizations—from top banks and fintechs to government agencies—we solve real, high-impact problems at scale. Come join us!
About The Role
Socure is looking for highly motivated AI Engineers to join our growing AI Platform team. This is an ideal opportunity for recent graduates from top-tier universities with a strong academic foundation and hands-on machine learning experience. You’ll contribute to building cutting-edge ML infrastructure and deploying models at scale, working alongside an innovative team of engineers and data scientists to power real-world fraud prevention solutions.
What You’ll Do
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Compensation Range: $115K - $140K
Using predictive analytics and advanced machine learning trained on billions of signals to power RiskOS, Socure has created the most accurate identity verification and fraud prevention platform in the world. Trusted by thousands of leading organizations—from top banks and fintechs to government agencies—we solve real, high-impact problems at scale. Come join us!
About The Role
Socure is looking for highly motivated AI Engineers to join our growing AI Platform team. This is an ideal opportunity for recent graduates from top-tier universities with a strong academic foundation and hands-on machine learning experience. You’ll contribute to building cutting-edge ML infrastructure and deploying models at scale, working alongside an innovative team of engineers and data scientists to power real-world fraud prevention solutions.
What You’ll Do
- Build Intelligent Systems: Design and maintain scalable ML pipelines for training, inference, and deployment across cloud infrastructure.
- Drive Feature Engineering: Develop and optimize feature engineering strategies to support high-performing models.
- Collaborate Across Teams: Partner with software engineers, data scientists, and product teams to expand ML capabilities.
- Implement MLOps Best Practices: Apply version control, model reproducibility, CI/CD workflows, and orchestration tools like Airflow or AWS Step Functions.
- Deploy Efficiently: Work with cloud platforms (AWS preferred) to automate, scale, and monitor production ML pipelines.
- Advance AI Innovation: Contribute to research initiatives and stay ahead of trends in GenAI, model monitoring, and AI-driven development.
- Academic Foundation: Bachelor’s or Master’s in Computer Science, AI, Machine Learning, or a related field from a top university with a strong GPA.
- Early Experience: 1–2 years of industry, co-op, or internship experience working on ML or AI applications.
- Technical Skills: Proficiency in Python; familiarity with ML frameworks like TensorFlow, PyTorch, or Scikit-learn.
- Cloud & Infrastructure: Experience with AWS (preferred), GCP, or Azure; knowledge of MLOps, Git, and model deployment.
- Pipeline & Data Know-how: Exposure to orchestration tools (Airflow, AWS Step Functions) and database technologies (SQL, NoSQL, Snowflake, Redshift).
- Core Competencies: Solid understanding of data structures, algorithms, and distributed systems. Strong analytical and problem-solving mindset.
- Experience with feature stores, Apache Spark, Kafka, or CI/CD for ML applications
- Familiarity with model monitoring tools and GenAI techniques (e.g., LLM fine-tuning, prompt engineering)
- Excellent communication and collaboration skills
- Growth mindset and willingness to seek feedback, iterate, and improve
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YouTube | LinkedIn | X (Twitter) | Facebook
Compensation Range: $115K - $140K
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