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Temporal Jobs in Massachusetts (NOW HIRING)

STR

Senior Research Scientist - Machine Leaning

Woburn, MA · On-site

$105K - $134K/yr

... or spatio-temporal data Company : STR is built on people & technology platforms tackling tough problems in cybersecurity, distributed sensing & artificial. Founded in 2010, the company is ...

STR

Data Scientist (CLEARANCE REQUIRED)

Woburn, MA · On-site

... or spatio-temporal data Company : STR is built on people & technology platforms tackling tough problems in cybersecurity, distributed sensing & artificial. Founded in 2010, the company is ...

STR

Data Scientist (CLEARANCE REQUIRED)

Woburn, MA · On-site

... or spatio-temporal data Company : STR is built on people & technology platforms tackling tough problems in cybersecurity, distributed sensing & artificial. Founded in 2010, the company is ...

SevenAI

Senior Software Engineer (Product)

Boston, MA · On-site

$133K - $175K/yr

Familiarity with Temporal or similar workflow engines. * Design sensibility - you don't need to be a designer, but you know when something isn't right. * Background in a product-facing or customer ...

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How much do temporal jobs pay per hour?

As of Aug 23, 2026, the average hourly pay for temporal in Massachusetts is $14.60, according to ZipRecruiter salary data. Most workers in this role earn between $10.48 and $17.07 per hour, depending on experience, location, and employer.

What is a Temporal engineer?

Temporal engineers are software professionals who specialize in using the Temporal platform to build, run, and scale reliable distributed applications. Temporal is an open-source workflow orchestration engine that helps developers manage complex workflows, handle failures, and ensure the consistency of long-running business processes. Temporal engineers design, implement, and maintain workflows that require coordination between multiple services, often in cloud-native environments. They use Temporal’s APIs and SDKs to build resilient applications that can recover from errors and interruptions automatically.

How does a Temporal engineer typically collaborate with cross-functional teams to deliver workflow solutions?

As a Temporal Engineer, collaboration with cross-functional teams is central to designing, implementing, and maintaining robust workflow solutions. You’ll frequently work alongside product managers, software engineers, and infrastructure teams to understand requirements and integrate Temporal's orchestration platform into broader system architectures. Regular meetings, code reviews, and design sessions are common, ensuring alignment on workflow logic and system reliability. This collaborative environment helps streamline communication, surface potential challenges early, and deliver scalable, dependable solutions.

What are the key skills and qualifications needed to thrive as a Temporal engineer, and why are they important?

To thrive as a Temporal Engineer, you need strong proficiency in distributed systems, software development (especially in Go or Java), and experience with workflow orchestration, ideally with a degree in computer science or a related field. Familiarity with Temporal's platform, cloud-native tools (like Kubernetes and Docker), and CI/CD systems is typically required. Excellent problem-solving, teamwork, and communication skills set top candidates apart in this role. These competencies ensure the reliable design, deployment, and operation of scalable workflow solutions, which are critical for modern software infrastructure.

What is the difference between Temporal vs Data Engineer?

AspectTemporalData Engineer
Required CredentialsTechnical knowledge of workflow orchestration, programming skillsDatabase, programming, and data pipeline skills
Work EnvironmentSoftware development, cloud-based systemsData processing, analytics, cloud platforms
Industry UsageWorkflow automation, microservices orchestrationData management, analytics, big data
Search & Comparison IntentUnderstanding workflow orchestration toolsData pipeline and infrastructure roles

Temporal is a workflow orchestration platform focused on managing complex application workflows, while Data Engineers build and maintain data pipelines and infrastructure for data processing. Both roles require technical skills but serve different purposes within software and data ecosystems.

Is Temporal a good company to work for?

Temporal is a technology company known for its open-source workflow orchestration platform. Employees often cite a collaborative environment, opportunities for growth, and a focus on innovation, though experiences can vary by role and team. As with any company, researching specific teams and roles can provide more insight into the work environment.

What are popular job titles related to Temporal jobs in Massachusetts?

For Temporal jobs in Massachusetts, the most frequently searched job titles are:

What job categories do people searching Temporal jobs in Massachusetts look for?

The top searched job categories for Temporal jobs in Massachusetts are:

Temporal jobs near you
Infographic showing various Temporal job openings in Massachusetts as of August 2026, with employment types broken down into 95% Full Time, 2% Part Time, 1% Temporary, and 2% Contract. Highlights an 81% Physical, 4% Hybrid, and 15% Remote job distribution, with an average salary of $30,367 per year, or $14.6 per hour.

Machine Learning Scientist - Clinical Prediction

Jobtailor

Boston, MA • On-site

$120 - $180/hr

Other

Posted 5 days ago

Job description

Responsibilities
  • Fine-tune large-scale multimodal transformer models for clinical and biomedical applications
  • Identify, characterize, and utilize datasets that deliver insights into pharmacokinetics (PK), pharmacodynamics (PD), toxicity, clinical adverse events, and clinical trial outcomes
  • Develop and apply rigorous experimental approaches that account for multiple sources of potential leakage (split, metadata, trial-family, temporal, ontological, arm-comparator, etc.)
  • Design and maintain benchmarking and evaluation frameworks that track model quality across models and tasks
  • Build models with appropriate calibration, uncertainty quantification, and clinically meaningful evaluation metrics
  • Collaborate with ML and software engineering colleagues to deploy and operationalize models
  • Partner with clinical scientists and pharmacologists to ensure model development is grounded in drug discovery and development needs
  • Communicate results to internal teams, external partners, and at conferences
  • Generate high-quality research and engineering code: refactor, test, document, and package ML components to support team velocity
Requirements
  • MS in chemistry, bio/chemical engineering, or a computational STEM field with 3+ years of relevant industry or research experience, or PhD or equivalent industry experience demonstrating comparable depth
  • Strong Python experience, including implementing and fine-tuning deep learning models
  • Demonstrated experience in clinical science or working with clinical datasets
  • Excellent Data Science skills (problem framing, data sourcing, extraction, cleaning, visualization, EDA, modeling, tuning, storytelling, etc.)
  • Enough independence to own a workstream from data ingestion through evaluation
  • Strong engineering habits: reproducible experimentation, appropriate control strategy, clean code, testing
  • Comfort working with modern ML infrastructure (e.g., Docker, CUDA, Kubernetes, experiment tracking such as Weights & Biases)
Hard Skills
  • multimodal transformer models
  • pharmacokinetics
  • pharmacodynamics
  • toxicology
  • clinical trial outcomes
  • experimental approaches
  • model calibration
  • uncertainty quantification
  • data science
  • deep learning
Soft Skills
  • collaboration
  • communication
  • independence
  • problem framing
  • storytelling
  • clean code
  • testing
  • organization
  • documentation
  • refactoring
Certifications & Qualifications
  • MS in chemistry
  • MS in bio/chemical engineering
  • PhD in computational STEM field
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