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Remote Databricks Jobs in Philadelphia, PA (NOW HIRING)

Arsenault Inc

Data Risk Analyst

Philadelphia, PA · Remote

$50 - $85/hr

Data Risk Analyst Remote 6 Month Contract $50-85 Hourly. An innovative company that is focused on ... Databricks understanding is a nice to have. * Ability to communicate effectively and efficiently.

Amerihealth Caritas

Sr Mgr IT

Newtown Square, PA · On-site +1

$125K - $125K/yr

Those fully remote associates residing in states where service is required by contract, law, or ... Drive Azure-based data engineering initiatives, including integration with Databricks, Azure Data ...

Carman Solutions Group

Azure Data Architect

Malvern, PA · Remote

$65 - $84.75/hr

Remote Duration: Long Term Contract Visa- Only US Citizen, H4 EAD, L2S, TN Visa Experience: 12 to ... Azure Databricks, ADF, Architecture, PySpark, SQL Mandatory Certification on Azure Architect ...

QVC

Data Engineer

West Chester, PA · Remote

$108K - $130K/yr

Where You'll Work This role is remote; job seekers must reside in one of the following states to be ... Experience using Azure tools (Databricks, Data Factory, Delta Lake, Synapse, ADLS, PySpark, SQL ...

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Remote Databricks information

What are the key skills and qualifications needed to thrive as a Remote Databricks Engineer, and why are they important?

To thrive as a Remote Databricks Engineer, you need a strong background in data engineering, cloud computing (especially Azure or AWS), and proficiency in languages like Python or Scala, often supported by a degree in computer science or a related field. Familiarity with Databricks platform tools, Spark, SQL, and relevant certifications such as Databricks Certified Data Engineer Associate are typically required. Strong problem-solving, communication, and self-motivation skills help you excel in remote and collaborative data-driven environments. These skills are essential for efficiently designing scalable data solutions and collaborating virtually to drive business value.

How does a remote Databricks engineer typically collaborate with cross-functional teams?

As a remote Databricks engineer, you will frequently work with data scientists, analysts, and other engineers through virtual collaboration tools such as Slack, Jira, and Zoom. Regular stand-up meetings, code reviews, and shared documentation platforms help maintain alignment across distributed teams. You'll often contribute to shared Databricks notebooks and participate in sprint planning to ensure data pipelines and analytics workflows meet business requirements. Effective communication and proactive documentation are key to successful remote collaboration in this role.

What are remote Databricks jobs?

Remote Databricks jobs are positions that involve working with the Databricks data analytics platform from a location outside of a traditional office, typically from home or another remote setting. These roles often focus on developing data pipelines, analyzing big data, building machine learning models, or managing cloud infrastructure using Databricks. Employees use collaboration tools and cloud-based environments to connect with their teams and access the Databricks platform securely. Remote Databricks jobs may be available for data engineers, data scientists, machine learning engineers, and DevOps professionals. The flexibility of remote work allows professionals to collaborate with global teams while leveraging Databricks’ powerful data processing and analytics capabilities.
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Remote Databricks jobs near you
Senior AI Engineer - Remote / Telecommute

Senior AI Engineer - Remote / Telecommute

CYNET SYSTEMS

Camden, NJ • Remote

$55 - $60/hr

Contractor

Re-posted 7 days ago

Job description

Job Overview:

Pay Range: $55/hr - $60/hr

Requirement/Must Have:

  • Expertise in LangChain, LlamaIndex, Semantic Kernel, AutoGen, or equivalent.
  • Strong experience with Unity Catalog, Delta Lake, Vector Search, Databricks Workflows, and Model Serving.
  • Hands-on with Lakehouse architecture patterns.
  • Experience with open-source LLMs (Llama, Mistral, etc.), prompting techniques, and fine-tuning approaches.
  • Strong knowledge of RAG architectures and embedding strategies.
  • Expertise in LangChain, LlamaIndex, Semantic Kernel, AutoGen, or equivalent.
  • Experience building agentic workflows and multi-agent systems.
  • Advanced Python proficiency (APIs, web apps, orchestration, data processing).
  • Familiarity with REST APIs and microservices architecture.
  • Experience with MLflow, CI/CD pipelines, model lifecycle management, and observability tools.
  • Knowledge of drift detection and model performance monitoring.
  • Experience with Spark, SQL, and large-scale data processing.
  • Familiarity with streaming frameworks (Kafka, Structured Streaming).
  • Expertise in AI security risks (prompt injection, jailbreaks, data leakage).
  • Experience implementing governance frameworks and compliance controls.

Responsibilities:

  • Build and orchestrate autonomous AI agents with multi-step reasoning, tool usage, and workflow chaining using frameworks like LangChain, CrewAI, AutoGen, Semantic Kernel, or LlamaIndex.
  • Deploy, fine-tune, and serve open-source LLMs (e.g., Llama 3) using Databricks Model Serving; optimize latency, throughput, and cost.
  • Design advanced RAG pipelines leveraging vector search, embeddings, semantic ranking, and enterprise data sources (structured + unstructured).
  • Develop prompt strategies, memory frameworks, and metadata tagging to improve contextual accuracy and response quality.
  • Build intuitive AI-driven applications using Databricks Apps (Streamlit/Dash) or modern web frameworks to enable business consumption.
  • Build reliable data pipelines (batch & streaming) supporting training, inference, and feature generation using Delta Lake.
  • Implement enterprise-grade controls using Unity Catalog (row/column-level security, lineage, auditability) aligned with compliance standards.
  • Implement guardrails (e.g., NeMo Guardrails) for prompt injection prevention, hallucination mitigation, and safe output handling.
  • Establish CI/CD pipelines for AI models and agents, including versioning, monitoring, drift detection, observability, and incident response.
  • Optimize model performance, GPU/compute usage, and inference cost efficiency across environments.
  • Testing & Evaluation.
  • Collaboration & Stakeholder Engagement.
  • Documentation & Knowledge Transfer.

Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading staffing and recruiting powerhouse. Proudly recognized as a nationally and locally certified diversity firm, Cynet delivers agile, scalable talent solutions across industries. With an active footprint in all 50 U.S. states and Canada, we support thousands of consultants through our expansive, high-performing recruitment engine operating across North America and Asia—ensuring speed, quality, and consistency in every hire.
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About Cynet Systems

Sourced by ZipRecruiter

Cynet Systems Inc is a staffing and recruiting corporation nestled in Ashburn, VA, USA. Established in 2010, the company operates within the Information Technology and Services sector, specializing in providing effective workforce solutions to different business needs, including IT consulting, direct hire, and contract staffing services. Through the years, Cynet Systems has built an impressive portfolio, going beyond borders and expanding its operations internationally in Canada and India. Rooted in its core values of teamwork, leadership, and commitment, Cynet Systems helps businesses unlock their full potential by providing versatile and competent professionals that perfectly align with their needs. Fueled by their unwavering mission to deliver top-tier talent to businesses worldwide, Cynet Systems garnered various recognitions including SIA's fastest-growing staffing firms and Best Place to Work in Virginia for 2019.

Industry

It services

Company size

501 - 1,000 Employees

Headquarters location

Sterling, VA, US

Year founded

2010

Social media

Twitter

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