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Remote Semantic Jobs in Boston, MA (NOW HIRING)

MatrixSpace

Machine Learning Engineer

Burlington, MA · Remote

$165K - $200K/yr

S. government security clearance in the future.' This is NOT a fully remote position! Required ... Experience with LangChain, LangGraph, LlamaIndex, AutoGen, Semantic Kernel, or similar frameworks.

Wsgr

Innovations and AI Solutions Engineer

Boston, MA · On-site +1

This position is available as a hybrid or remote work schedule. Essential Duties, Responsibilities ... Experience with vector databases and embeddings for semantic search and retrieval-augmented ...

apiphani

Senior Software Engineer (AI / LLMs)

Boston, MA · Remote

$120K - $160K/yr

Remote | Full-time | Competitive Compensation Apiphani is building the future of intelligent ... Develop data access and semantic search layers using vector databases (e.g., pgvector, Pinecone ...

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All JobsSemantic JobsRemote Semantic JobsRemote Semantic Jobs in Boston, MA

Remote Semantic information

See Boston, MA salary details

$90.7K

$138K

$185.8K

How much do remote semantic jobs pay per year?

As of Sep 5, 2026, the average yearly pay for remote semantic in Boston, MA is $138,007.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,400.00 and $155,900.00 per year, depending on experience, location, and employer.

What is a remote semantic job?

Remote semantic jobs involve working with the meaning and interpretation of language, often in the context of natural language processing (NLP), artificial intelligence, or data analysis, but performed from a remote location. These roles may include tasks such as semantic annotation, ontology development, or improving search and recommendation systems. Professionals in these jobs typically use linguistic, analytical, and technical skills to help computers better understand human language. Remote semantic jobs are common in tech companies, research institutions, and organizations focused on language technologies.

What are the key skills and qualifications needed to thrive as a remote semantic analyst?

To thrive as a Remote Semantic Analyst, you need a strong background in linguistics, data analysis, and natural language processing, often supported by a relevant degree. Familiarity with semantic annotation tools, machine learning platforms, and programming languages like Python is commonly required. Attention to detail, critical thinking, and effective remote communication are crucial soft skills in this role. These competencies ensure accurate analysis and interpretation of language data, supporting the development of advanced AI and search technologies.

What are some common challenges faced by professionals working in remote semantic analysis roles, and how can they be addressed?

Professionals in remote semantic analysis roles often encounter challenges such as limited direct communication with colleagues, managing large and complex datasets, and maintaining alignment on project goals. To address these, it's important to proactively engage in regular virtual meetings, utilize collaborative tools for version control and annotation, and establish clear documentation standards. Building strong communication habits and staying updated on the latest semantic technologies can also help remote teams stay efficient and aligned.

What is the difference between Remote Semantic vs Remote Data Analyst?

AspectRemote SemanticRemote Data Analyst
Required CredentialsBachelor's in Linguistics, Computer Science, or related fields; knowledge of semantic technologiesBachelor's in Statistics, Mathematics, or related fields; proficiency in data analysis tools
Work EnvironmentCollaborative teams, often in tech or AI companies, remote or hybridData-focused teams, in tech, finance, or healthcare sectors, remote or hybrid
Employer & Industry UsageTech companies, AI startups, NLP projectsBusiness, finance, healthcare, tech industries
Common Search & ComparisonYesNo

Remote Semantic professionals focus on understanding and applying semantic technologies, often in NLP and AI projects, requiring linguistics or computer science credentials. Remote Data Analysts analyze data sets to inform business decisions, requiring strong statistical skills. While both roles can be remote and work in tech environments, their core skills and industry applications differ significantly.

What are popular job titles related to Remote Semantic jobs in Boston, MA?

For Remote Semantic jobs in Boston, MA, the most frequently searched job titles are:

What job categories do people searching Remote Semantic jobs in Boston, MA look for?

The top searched job categories for Remote Semantic jobs in Boston, MA are:

What cities near Boston, MA are hiring for Remote Semantic jobs?

Cities near Boston, MA with the most Remote Semantic job openings:

Remote Semantic jobs near you

Data Solutions Architect

SMART TECH SKILLS LLC

Marlborough, MA • Remote

Full-time

Posted 3 days ago

New

Job description

Benefits:
  • Competitive salary

Location
Remote (U.S.-based) / Hybrid options available
Experience Level
Senior–Lead Level (10 or more years of data architecture and engineering experience)
Role Overview
The Data Solutions Architect leads the design, architecture, and implementation of enterprise-scale data platforms across Azure, AWS, and multi-cloud environments. This role defines modern data strategies, establishing robust Lakehouse and Data Warehouse solutions that support business intelligence, advanced analytics, and AI/ML initiatives. Working closely with engineering teams and executive stakeholders, the Data Solutions Architect builds scalable, secure, and performant data ecosystems to enable data-driven decision-making across the organization.
Key Responsibilities
Enterprise Architecture & Strategy
  • Define enterprise data platform strategies, architectural blueprints, and engineering standards.
  • Design scalable, secure Lakehouse and Data Warehouse architectures supporting both structured and unstructured data.
  • Implement dimensional data models, star and snowflake schemas, and scalable ingestion frameworks.
  • Align modern data architecture initiatives with organizational business goals and digital transformation roadmaps.

Data Pipeline & Platform Engineering
  • Architect high-performance, resilient batch and real-time data pipelines using PySpark, Databricks, Kafka, and cloud-native services.
  • Implement end-to-end data ecosystems integrating Azure Data Factory, ADLS Gen2, Azure Synapse Analytics, Snowflake, and AWS data services.
  • Optimize platform performance through partitioning strategies, clustering, data skew remediation, schema evolution, and distributed workload tuning.

Data Governance, Security, & Quality
  • Establish comprehensive data governance, metadata management, schema management, and data quality frameworks.
  • Implement automated data validation, observability, and compliance monitoring across all data pipelines.
  • Enforce cloud security best practices, role-based access controls, and data protection standards across multi-cloud environments.

DevOps, Automation, & Analytics Integration
  • Automate cloud infrastructure deployments using Terraform (Infrastructure as Code) and CI/CD pipelines via Azure DevOps.
  • Integrate modern business intelligence and enterprise reporting tools, including Power BI, to deliver actionable insights.
  • Collaborate with engineering, analytics, business, and executive stakeholders to drive architectural excellence and continuous delivery.

Required Qualifications
  • 10 or more years of experience in data engineering, data platform architecture, and enterprise software delivery.
  • 5 or more years of experience architecting and implementing modern cloud data platforms on Azure, AWS, or multi-cloud environments.
  • Strong hands-on architectural experience with Azure data services, including Azure Databricks, Azure Data Factory, ADLS Gen2, and Azure Synapse Analytics.
  • Deep expertise in Lakehouse and Data Warehouse design using Snowflake and Databricks.
  • Extensive experience designing distributed processing pipelines using PySpark, SQL, and streaming technologies like Apache Kafka.
  • Proven experience in dimensional modeling, schema design, and query performance optimization techniques.
  • Experience establishing data governance, metadata catalogs, and automated data quality validation frameworks.
  • Proficiency with Infrastructure as Code (Terraform) and CI/CD automation tools.

Preferred Qualifications
  • Experience architecting data platforms that support machine learning, advanced analytics, and AI/ML workloads.
  • Hands-on experience with AWS data services, including AWS Glue, AWS Lambda, and S3.
  • Advanced knowledge of enterprise reporting and semantic layer modeling using Power BI.
  • Relevant cloud or architecture certifications (e.g., Azure Solutions Architect, Databricks Certified Architect, or Snowflake SnowPro).

Core Skills & Attributes
  • Exceptional ability to translate complex business objectives into scalable, high-performing technical architectures.
  • Strong strategic thinking with expertise in workload optimization, cost governance, and distributed system resilience.
  • Excellent communication and presentation skills across executive, technical, and non-technical audiences.
  • Proven technical leadership with the ability to mentor data engineers and establish engineering best practices.

This is a remote position.