javascript developer salaries in washington, district of columbia

job summary: Our client in Washington, DC is seeking a highly skilled and hands-on Lead AI/ML Engineer to drive the design, development, and deployment of advanced machine learning and generative AI solutions. This role will serve as a technical leader, guiding cross-functional teams in building scalable, high-performing AI/ML systems across a modern cloud-native environment. The ideal candidate will bring deep expertise in supervised/unsupervised learning, MLOps, large language models, and modern coding practices, while also mentoring junior engineers and shaping platform-wide AI capabilities.   location: Washington, Washington, D.C. job type: Contract salary: $30 - 40 per hour work hours: 9am to 5pm education: Bachelors   responsibilities: Design and implement machine learning models including regression, classification, clustering, time-series forecasting, and boosting algorithms Build and optimize neural networks (CNNs, RNNs, LSTMs) for diverse data and use cases Develop and integrate Generative AI solutions using LLMs and foundation models; apply techniques like prompt engineering, LoRA, and PEFT Write advanced, production-grade Python code; develop in JupyterLab and VSCode Deploy solutions using Docker, Kubernetes, and cloud platforms (AWS, Azure); manage version control with Git Manage the end-to-end ML lifecycle including model serialization (Pickle, Joblib, ONNX), API deployment with FastAPI, and serverless infrastructure Build internal tools and AI interfaces using Streamlit and modern front-end technologies (HTML/CSS/JavaScript) Champion Databricks adoption to enable AutoML, pipeline automation, and scalable development Perform robust data processing, visualization, and storytelling using tools like pandas, polars, NumPy, scikit-learn, seaborn, and PyTorch Mentor junior team members, foster self-service AI/ML capabilities, and collaborate across teams to align technical solutions with business goals  qualifications: 7+ years of experience in data science, machine learning, or AI engineering Proven experience leading AI/ML solution delivery in a production environment 3+ years of hands-on experience with deep learning frameworks (e.g., PyTorch, TensorFlow) Strong background in Python programming and ML libraries (scikit-learn, pandas, NumPy) Experience deploying models in cloud environments (AWS, Azure) using Docker and Kubernetes Proficiency with MLOps practices and tools such as MLflow, FastAPI, and ONNX Familiarity with Databricks and Spark for large-scale data processing and modeling Experience building and deploying Generative AI solutions using LLMs and foundation models Bachelor's or Master's degree in Computer Science, Data Science, or related field Relevant certifications (e.g., AWS Certified Machine Learning - Specialty, Databricks ML Professional, Google Cloud ML Engineer) preferred  skills: Team Leadership and Mentorship - Ability to lead and guide junior engineers and data scientists Strong Communication Skills - Able to explain technical concepts to both technical and non-technical stakeholders Problem Solving and Critical Thinking - Skilled at analyzing complex problems and designing scalable solutions Collaboration and Cross-Functional Teamwork - Experience working across business, data, and engineering teams Programming Proficiency - Advanced skills in Python and experience with code versioning tools like Git Cloud Computing Knowledge - Familiarity with AWS, Azure, or GCP environments for AI/ML deployment Machine Learning Expertise - Deep understanding of algorithms, model tuning, and performance optimization MLOps and Model Deployment - Ability to operationalize models using tools like FastAPI, Docker, and Kubernetes Generative AI and LLMs - Understanding and hands-on experience with large language models and prompt engineering Data Visualization and Storytelling - Capable of translating data insights into clear visual narratives for stakeholders 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 HRsupport@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.

job summary: We are seeking a highly skilled Real-Time Data Streaming Engineer to join a dynamic team supporting one of Randstad's premier clients in Washington, DC. This role requires deep experience in building and managing event-driven architectures and real-time data pipelines using modern streaming and orchestration tools. The ideal candidate has a passion for distributed systems, excels in handling high-throughput data pipelines, and is comfortable working across cloud-native environments with a focus on performance, security, and scalability.   location: Washington, Washington, D.C. job type: Contract salary: $35 - 40 per hour work hours: 9am to 5pm education: Associates   responsibilities: Design, build, and maintain real-time data pipelines using Apache Kafka, Amazon MSK, Kafka Streams, and Kafka Connect Implement and optimize stream processing solutions using Apache Flink, Spark Streaming, or similar frameworks Manage data workflows and orchestration using Apache NiFi and Apache Airflow Administer and integrate messaging platforms such as MQ and Pub/Sub systems to support event-driven microservices Architect and support scalable, cloud-native streaming infrastructure across AWS, GCP, or Azure environments Implement best practices for schema evolution, data governance, and secure data processing Collaborate with cross-functional engineering teams to develop event-based microservices and integrations Troubleshoot and resolve issues related to stream processing performance and reliability Contribute to the continuous improvement of infrastructure, deployment automation, and monitoring solutions Stay current on emerging technologies and help drive innovation in real-time data architecture and tooling  qualifications: Minimum of 6 years of hands-on experience in data engineering, stream processing, or event-driven architecture 3+ years of experience working with Apache Kafka and/or Amazon MSK in production environments Proven experience with real-time data frameworks such as Apache Flink or Spark Streaming Experience with data workflow tools such as Apache NiFi and Apache Airflow Strong understanding of distributed systems and streaming data semantics Proficiency in working with cloud platforms such as AWS, Azure, or GCP Familiarity with containerization and orchestration tools like Docker and Kubernetes Experience with schema management, data governance, and compliance in streaming systems Bachelor's degree in Computer Science, Engineering, or related technical field (Master's preferred) Relevant certifications (e.g., Confluent Certified Developer for Apache Kafka, AWS Certified Data Analytics - Specialty) are a plus  skills: Team Player - Collaborates effectively across cross-functional teams Strong Problem Solver - Quickly diagnoses and resolves complex technical issues Great Communicator - Clearly conveys technical concepts to both technical and non-technical audiences Programming - Proficient in languages such as Java, Scala, or Python for stream processing Requirements Gathering - Accurately captures and interprets business and technical requirements Cloud Computing - Skilled in cloud platforms like AWS, Azure, or GCP System Design - Capable of designing scalable, event-driven data architectures Security Awareness - Understands data privacy, governance, and compliance principles Continuous Learner - Keeps up with emerging technologies and best practices Automation Mindset - Seeks to streamline processes through scripting and tool integration 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 HRsupport@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.

job summary: Our Randstad client in Washington, DC is seeking a Data Quality Automation Engineer to lead the design and implementation of automated data validation, profiling, and anomaly detection pipelines. This role will play a critical part in ensuring data integrity across modern data platforms including Databricks, SAP DataSphere, and Informatica Cloud. The ideal candidate will have strong technical skills in Python and SQL, a solid understanding of data governance, and experience working cross-functionally with engineering, governance, and business teams to embed quality and compliance into every stage of the data lifecycle.   location: Washington, Washington, D.C. job type: Contract salary: $28 - 34 per hour work hours: 9am to 5pm education: Associates   responsibilities: Design and implement scalable, automated data quality pipelines to proactively identify and resolve data issues Build reusable components for anomaly detection, rule enforcement, and schema validation Translate data governance policies (e.g., certified sources, critical fields) into enforceable technical rules Integrate quality checks across tools like Databricks, SAP DataSphere, and Informatica Cloud, while remaining adaptable to evolving tech stacks Partner with data engineers, governance teams, analysts, and product owners to align quality expectations and deliver trusted data Track, document, and report on data quality metrics, including rule compliance and issue resolution Leverage tools such as Great Expectations or AWS Deequ to implement data quality frameworks Use Python and SQL to create profiling scripts and validation logic Support enterprise adoption of certified datasets and enforce ownership and stewardship rules Promote a culture of data accountability by embedding data health metrics into engineering workflows  qualifications: 5+ years of experience in data engineering, data quality, or data governance roles Strong proficiency in Python and SQL for data validation and pipeline development Hands-on experience with data quality frameworks such as Great Expectations, Deequ, or similar tools Prior experience working with modern data platforms such as Databricks, SAP DataSphere, and Informatica Cloud Experience integrating data quality checks into CI/CD workflows and modern data pipelines Familiarity with cloud data ecosystems (AWS, Azure, or GCP) Working knowledge of data governance principles, including critical data elements, certified datasets, and ownership models Bachelor's or Master's degree in Computer Science, Data Science, Information Systems, or related field Experience operationalizing data health metrics and quality dashboards for technical and business stakeholders Preferred certifications: Microsoft Azure Data Engineer Associate AWS Certified Data Analytics - Specialty Informatica Data Quality Developer Certification Databricks Lakehouse Fundamentals   skills: Programming Proficiency - Strong skills in Python and SQL Data Quality & Profiling Expertise - Experience with data validation and anomaly detection Cloud Platform Knowledge - Familiarity with AWS, Azure, or GCP Tool Flexibility - Comfortable working with tools like Databricks, SAP DataSphere, and Informatica Problem Solving - Strong analytical and troubleshooting capabilities Collaboration - Works effectively with cross-functional teams Communication Skills - Able to explain technical concepts to non-technical stakeholders Requirements Gathering - Skilled at translating business needs into technical quality rules Automation Mindset - Focus on scalable, reusable quality solutions Attention to Detail - Consistently ensures data accuracy and integrity across systems 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 HRsupport@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.