Big Data/Machine Learning Engineer

job summary:
Randstad Digital is hiring and we're looking for someone like YOU to join our team! If you are seeking a new opportunity, looking to grow in your career, or you know someone who is - we want to hear from you! Take a look at the below opportunity, or feel free to visit RandstadUSA.com to view and apply.

 
location: Richmond, Virginia
job type: Contract
salary: $67.19 - 74.36 per hour
work hours: 8am to 5pm
education: Bachelors

responsibilities:

Data Engineering & Big Data Architecture:

• Design, build, and maintain high-throughput streaming and batch data processing pipelines to support training data preparation and feature generation at scale.
• Manage big data storage, transformation, and querying frameworks across multi-terabyte dataset systems.

Machine Learning & Feature Engineering:

• Implement feature engineering processes and feature store architectures ensuring training-serving consistency.
• Convert research-level ML prototypes into optimized, scalable production code.
• Fine-tune, benchmark, and scale traditional ML, Deep Learning, or Generative AI models for real-time and batch inference.

MLOps, Deployment & Infrastructure:

• Build and maintain robust MLOps framework tools, continuous training (CT) pipelines, and CI/CD pipelines for automated deployment.
• Expose ML models via REST/gRPC microservices, ensuring low-latency inference and target availability SLA compliance.
• Implement comprehensive model monitoring tools for data drift, concept drift, system performance, and output quality checks.

Technical Leadership & Governance:

• Mentor junior and mid-level engineers, enforcing software engineering best practices across data and ML codebases.
• Ensure system compliance with enterprise security, data privacy, and AI governance standards.

qualifications:
Experience: 5+ years of software engineering, big data engineering, and applied machine learning engineering experience in production environments.Programming Languages: Advanced proficiency in Python and Scala or Java. Big Data Frameworks: Hands-on experience with Apache Spark (PySpark/Scala), Kafka, Flink, Hadoop, Databricks, or Snowflake.Machine Learning Frameworks: Proficiency with frameworks like PyTorch, TensorFlow, scikit-learn, or XGBoost. MLOps & DevOps: Experience with MLflow, Kubeflow, Feature Stores (e.g., Feast, Hopsworks), Docker, Kubernetes, and CI/CD automation.Cloud Architecture: Deep experience with AWS (S3, SageMaker, EMR), GCP (BigQuery, Vertex AI, Dataflow), or Azure (Databricks, Synapse).Databases & Storage: Mastery of SQL, NoSQL databases (Cassandra, MongoDB), and Vector Databases (Pinecone, Milvus, Qdrant). Education: Bachelor's or Master's degree in Computer Science, Data Science, Software Engineering, or a related quantitative field.

skills:
S3,experience with AWS,Flink,Hadoop,Kafka,Apache Spark,AI,Big Data,BigQuery,Cassandra,Cloud Architecture,Dataflow,data quality frameworks,data processing pipelines,Databases,Databricks,Deep Learning,DeepSpeed,automated deployment,DevOps,distributed data,Docker,concept drift,feature generation,Feature Engineering,Feature Stores,Generative AI models,Generative AI,Great Expectations,Data Engineering,Computer Science,Java,Kubeflow,Kubernetes,Large Language Models,LLMs,Machine Learning,ML models,applied machine learning,ML infrastructure,MLOps,MLflow,Megatron,microservices,Azure,Milvus,MongoDB,NoSQL databases,Ollama,Pinecone,production code,Programming Languages,PySpark,proficiency in Python,PyTorch,Qdrant,RAG,SQL,scikit-learn,Snowflake,software engineering best practices,software engineering,Machine Learning Frameworks,TensorFlow,training data,XGBoost,resilient,data drift,Architecture,automation,continuous training,enterprise security,prototypes,data privacy,Deequ,Data Science,Vertex AI,Governance,AI governance,Infrastructure,system compliance,Mentor,model training,production systems,quality checks,system implementation,Technical Leadership,Vector Databases

Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.

At Randstad Digital, we welcome people of all abilities and want to ensure that our hiring and interview process meets the needs of all applicants. If you require a reasonable accommodation to make your application or interview experience a great one, please contact View email address on randstadusa.com.


Pay offered to a successful candidate will be based on several factors including the candidate's education, work experience, work location, specific job duties, certifications, etc. In addition, Randstad Digital offers a comprehensive benefits package, including: medical, prescription, dental, vision, AD&D, and life insurance offerings, short-term disability, and a 401K plan (all benefits are based on eligibility).

This posting is open for thirty (30) days.