ZipRecruiter

Log In

2

Remote Machine Learning Compiler Engineer Jobs in Puerto Rico

Infotech Sourcing

Linguist III

PR · Remote

Infrastructure Engineering - Linguist III Location: US - NY - Remote Duration:8 months Job Title ... machine learning, NLP, or software engineers, or data scientists Experience contributing to ...

Cognizant Technology Solutions

$100K - $132K/yr

... Remote Serve as a Senior Engineer - Execution Systems in a hybrid work environment, designing ... learning and staying current with AVEVA PI and industrial data trends. Job Details Job Title:

Huntington

Lead ETL Developer

Florida, PR · On-site +1

If you consider data as a strategic asset and have a passion for learning and continuous ... Remote roles will also have the opportunity to come together in our offices for moments that matter.

ABB

Service Sales Specialist

Aguadilla, PR · Remote

... learning, and creative problem-solvingthat allows the right candidate to handle multiple work ... Remote {#LI-Remote}, this role provides support for the East Coast and will require East Coast ...

All JobsMachine Learning Compiler Engineer JobsRemote Machine Learning Compiler Engineer JobsRemote Machine Learning Compiler Engineer Jobs in Puerto Rico

Remote Machine Learning Compiler Engineer information

How does a Remote Machine Learning Compiler Engineer typically collaborate with cross-functional teams to optimize model deployment?

As a Remote Machine Learning Compiler Engineer, you will frequently collaborate with data scientists, hardware engineers, and software developers to ensure that machine learning models are efficiently compiled and deployed on target platforms. Communication often takes place through virtual meetings, code reviews, and shared documentation tools. You'll be responsible for translating research models into optimized code, troubleshooting performance bottlenecks, and integrating feedback from various stakeholders. Effective teamwork is crucial, as the success of deployments often depends on iterative feedback and close alignment with both the ML research and hardware teams.

What is a Remote Machine Learning Compiler Engineer?

A Remote Machine Learning Compiler Engineer is a software engineer who specializes in developing and optimizing compilers specifically for machine learning workloads, while working from a remote location. Their primary responsibilities include designing and implementing compiler features that translate machine learning models into efficient code for various hardware platforms, such as CPUs, GPUs, or specialized accelerators. They collaborate closely with machine learning researchers, hardware engineers, and software developers to ensure high performance and compatibility. In addition to strong programming skills, they typically require expertise in compiler theory, machine learning frameworks, and hardware architectures. This role allows for flexible, location-independent work while contributing to cutting-edge AI technologies.

What is the difference between Remote Machine Learning Compiler Engineer vs Remote Data Scientist?

AspectRemote Machine Learning Compiler EngineerRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Software Engineering, or related fields; knowledge of compiler design and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in programming, statistics, and data analysis
Work EnvironmentPrimarily software development, compiler optimization, and ML model deploymentData analysis, model building, and interpretation of results
Industry UsageTech companies, AI startups, hardware firms focusing on ML hardware accelerationTech, finance, healthcare, and research organizations

While both roles involve working with machine learning, the Remote Machine Learning Compiler Engineer focuses on developing and optimizing compilers for ML models, whereas the Remote Data Scientist concentrates on analyzing data and building predictive models. The roles share some technical skills but differ in their core responsibilities and work environments.

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

To thrive as a Remote Machine Learning Compiler Engineer, you need a strong background in computer science, proficiency in programming languages like C++ and Python, and expertise in compiler theory and machine learning frameworks. Familiarity with ML compilers such as TVM or XLA, and experience using version control and CI/CD systems are commonly required, along with a relevant bachelor's or master's degree. Outstanding problem-solving, collaboration, and communication skills are essential for working effectively in distributed teams and across technical domains. These skills and qualities enable the development of efficient, scalable ML solutions that bridge software and hardware, ensuring high performance and innovation.
What are popular job titles related to Remote Machine Learning Compiler Engineer jobs in Puerto Rico? For Remote Machine Learning Compiler Engineer jobs in Puerto Rico, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning Compiler Engineer jobs in Puerto Rico look for? The top searched job categories for Remote Machine Learning Compiler Engineer jobs in Puerto Rico are:
What cities in Puerto Rico are hiring for Remote Machine Learning Compiler Engineer jobs? Cities in Puerto Rico with the most Remote Machine Learning Compiler Engineer job openings:
Remote Machine Learning Compiler Engineer jobs near you
Infographic showing various Remote Machine Learning Compiler Engineer job openings in Puerto Rico as of June 2026, with employment types broken down into 87% Full Time, 8% Part Time, 2% Temporary, and 3% Contract. Highlights an 52% Physical, 3% Hybrid, and 45% Remote job distribution.
Linguist III

Linguist III

Infotech Sourcing

PR • Remote

Other

Posted 25 days ago

Job description

Job Title: Infrastructure Engineering - Linguist III
Location: US - NY - Remote
Duration:8 months
Job Title: Linguist lII (FAIR)
Main duties:
Perform linguistic analyses on large datasets.
Perform linguistic error analysis of AI model outputs, determining what the most frequent and severe error categories are.
Write and revise guidelines for human annotation and other AI projects, including but not limited to translation tasks.
Conduct typological and sociolinguistic research on a large number of languages, highlighting their similarities and differences.
Perform linguistic analyses for Responsible AI (toxic language, hate speech, gender bias and other cultural biases) in massively multilingual settings.
Conduct linguistic literature reviews on various NLP-adjacent topics, and summarize findings.
Compare the quality of deliveries between vendors, identify error patterns, and provide actionable feedback.
Provide information or guidance relative to any aspect of linguistic knowledge (typology, morpho-syntax, sociolinguistics, classification, phonetics/phonology, pragmatics, etc.).
Reach out to and collaborate with native speakers in various languages.
Communicate results of linguistic analyses to engineers and research scientists.
Skills:
Must have strong written and spoken communication skills, especially business and research communication.
Must be a native speaker of a non-English language (preferably Hindi) with a high level of proficiency in another Indo-Aryan or South Dravidian language, plus broad knowledge of other languages in either of those two groups.
Working knowledge in other languages is a plus. Proficiency in a low-resource language is valued.
Must be able to code in Python (must) and query databases using SQL, other coding languages used for data analysis are a plus.
Must be able to independently work through complex requests and perform under pressure.
Strong ability to work independently, prioritize, plan, and track work, as well as report progress
education or training in the basics of project management is a plus
self-motivation is a must
Working knowledge of international language-classification standards is valued.
Education:
Graduate degree in Linguistics or related field is a must; PhD is a plus
a background or specialization in corpus linguistics is a plus
experience with field work is a plus
a graduate degree in Literature or English is not an appropriate substitution
degree in Computer Science with a specialization in NLP is not an appropriate substitution
Must have a very firm grasp of the following linguistic fields: language typology, syntax, morphology, sociolinguistics (especially dialectology and discourse analysis), corpus linguistics, writing systems, pragmatics, phonology.
Must have some experience with applying basic Natural Language Processing techniques.
Experience
Years of experience: 0-3
Experience working cross-functionally
Experience collaborating with machine learning, NLP, or software engineers, or data scientists
Experience contributing to research papers
Important: Preferably no known conflicts of interest in the fields of machine translation, ASR, TTS, or LLM research (as FAIR Linguists need to be contributing to research papers)

Apply