Austin, TX

Data Jobs in Austin, TX

47 jobs found

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Today

Sr. SW AI Engineer

Visa Technology and Operations LLC Austin, TX

Austin, TX

Today

$111k - $172k/yr Full time Backend Developer Agentic Ai Ai Agent

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Job Description

Sr. SW AI Engineer role on Visa’s AI-first engineering team, building production-grade agentic systems powered by LLMs.

Responsibilities

Collaborate with stakeholders to interpret requirements for project components and incorporate feedback into future designs or solution fixes.
Verify assumptions while translating business requirements; escalate potential design issues to appropriate stakeholders.
Participate in system design and architecture, refining code plans and contributing to design documentation.
Support project estimation and escalate risks that may cause delays.
Develop, implement, and maintain code for products, services, or components using coding patterns, guidelines, and best practices.
Use debugging tools to validate assumptions and proactively flag issues before they occur.
Participate in code reviews to ensure coding standards are followed and handle routine pull requests.
Create test plans and configure testing procedures to identify and resolve defects across multiple features.
Respond to support requests during on-call rotations, troubleshooting issues and deploying fixes under guidance.
Leverage and build knowledge of software developer tools to create, debug, and maintain code for components.
Invest time in training resources to improve product availability, reliability, efficiency, observability, and performance.
Design, implement, and tune multi-agent LLM workflows using orchestration frameworks such as LangGraph, LangGraph4j, and LangChain4j, including declarative graph compilation, conditional routing, state persistence, and dynamic agent spawning.
Build and maintain ReAct agent loops (iterative Reason Act- Observe cycles) where an LLM selects tools, interprets tool results, and continues until a terminal answer is produced.
Implement Supervisor/Orchestrator agent patterns where a Lead Agent dynamically plans, spawns, and coordinates Specialist Sub-Agents using conditional graph edges and tool frameworks.
Develop MCP (Model Context Protocol) tool servers that expose enterprise data sources as callable tools for AI agents.
Implement and refine RAG pipelines: document ingestion and chunking (PDF/Word), embedding generation, vector storage (e.g., PostgreSQL + pgvector), and semantic similarity retrieval to ground responses in authoritative documents.
Integrate with enterprise LLM inference gateways via REST APIs, including request shaping, prompt template management, token budget control, and graceful degradation under service unavailability.
Design agent memory architectures: short-term per-agent isolated context stores and long-term shared knowledge repositories across workflows.
Implement confidence scoring and uncertainty quantification for AI-generated outputs, including threshold-based routing of low-confidence results to human review.
Build agent feedback loops by capturing human reviewer decisions and feeding structured corrections back into prompt templates and knowledge repositories.
Write LangChain4j / LangChain tool definitions (e.g., Java @Tool-annotated methods) and wire them into ReAct agents for data transformation, external API calls, and domain processing.
Build and maintain agentic audit trails with structured logs capturing tool calls, agent decisions, LLM prompt/response, and state transitions for traceability and explainability.
Develop and test Spring Boot microservices (Java 21, Spring Boot 3.5.x) to host AI orchestration engines, expose REST APIs, and integrate with upstream data source systems.
Author Helm charts and Jenkins CI/CD pipelines for containerized deployment of AI services to Kubernetes/OpenShift across multi-region on-premise data centers.
Develop and test end-to-end and integration tests for non-deterministic AI components, including prompt regression suites, tool call mock frameworks, agent output schema validators, and determinism gates to catch silent prompt drift.

Requirements

2+ years of work experience with a Bachelor’s Degree or an Advanced Degree (e.g., Masters, MBA, JD, MD, PhD).
OR 3+ years of work experience with a Bachelor’s Degree, OR more than 2 years with an Advanced Degree (e.g., Masters, MBA, JD, MD).
OR 2+ years relevant work experience with a Bachelor’s degree, OR 5+ years relevant work experience.
Experience in technologies/software systems or a directly related field (minimum two years).
Experience developing and/or implementing web-based or mobile applications (minimum two years).
Experience in system design and architecture for product components.
Experience in debugging and troubleshooting software issues.
Experience in code review and applying coding standards.
Experience in test planning and execution for software features.
Experience in responding to support requests and deploying fixes.
Experience using software developer tools for code creation and maintenance.
Experience developing backend services in Java (Java 17+ preferred; Java 21 a strong plus).
Familiarity with REST API design, Spring Boot, and JPA/ORM-based data access patterns.
Foundational understanding of LLM APIs: prompt construction, token limits, and response parsing.
Experience building and testing enterprise-scale web services (minimum one year).
Experience working on client-facing project or technical teams (minimum one year).
Experience integrating feedback into design and solution fixes.
Experience mentoring junior engineers and collaborating with cross-functional teams.
Hands-on experience building agentic AI systems using LangGraph, LangChain, LangGraph4j, or LangChain4j, including multi-agent graph construction, node/edge definitions, conditional routing, and state schema design.
Experience implementing the React prompting pattern (Thought Action- Observation) in a production or near-production LLM application.
Working knowledge of MCP: server registration, tool schema definition (tools/list, tools/call), and client-side integration.
Experience building RAG pipelines: document chunking strategies, embedding models, vector database querying (pgvector, Pinecone, Weaviate, or equivalent), and retrieval relevance tuning.
Experience with prompt engineering, including structured output enforcement (JSON schema), chain-of-thought prompting, few-shot example design, and system prompt management.
Experience building and monitoring LLM observability (token usage, latency per agent step, tool call success rates, output quality metrics).
Experience with PostgreSQL including pgvector for embedding storage and similarity search.
Experience deploying containerized workloads on Kubernetes or OpenShift, including Helm chart authoring, rolling deployments, and health probes.
Experience designing audit logging for AI agent decisions with structured, queryable formats capturing inputs, reasoning traces, tool calls, and outputs.
Familiarity with Aspect-Oriented Programming (AOP) for cross-cutting concerns in Spring Boot (agent call logging, latency measurement, security enforcement).
Experience with CI/CD pipelines (Jenkins or equivalent) for AI/ML service deployments, including version gating and environment promotion strategies.

Technologies

Generative AI tools (e.g., ChatGPT, Microsoft Copilot)
Large language models (LLMs)
LangGraph, LangGraph4j, LangChain4j, LangChain
ReAct (Reasoning + Acting)
Model Context Protocol (MCP)
REST APIs
RAG (Retrieval-Augmented Generation)
PostgreSQL, pgvector
JPA/ORM
Spring Boot, Java (Java 21), Spring Boot 3.5.x
Helm charts, Jenkins CI/CD pipelines
Kubernetes, OpenShift
PDF, Word
JSON schema
Aspect-Oriented Programming (AOP)
Pinecone, Weaviate

Benefits

Medical
Dental
Vision
401(k)
FSA/HSA
Life Insurance
Paid Time Off
Wellness Program

Work Details

Location: Austin, TX (onsite)
Salary: USD 110,700 - 171,800 per yearly
Work hours: Varies upon the needs of the department
Travel: 5-10% of the time
Work setting: Office setting; sit/stand at a desk; communicate in person and by telephone; frequently operate standard office equipment (telephones and computers)

Compensation Information for US Applicants

Estimated salary range: $110,700.00 to $171,800.00 USD per year
May include potential sales incentive payments (if applicable)
Position may be eligible for bonus and equity

Information for Us Applicants

Job family: Sr. SW AI Engineer

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17d ago

Data Engineer, Demand Planning

Tesla Austin, TX

Austin, TX

17d ago

Full time Data Engineer Data Integration Data Pipeline

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Job Description

Join Tesla as a Data Engineer, Demand Planning and help power forecasting, production planning, and deployment logistics across the energy business. This onsite role in Austin, TX focuses on building scalable modules and data pipelines that support optimization tools used for planning decisions across Tesla manufacturing facilities worldwide.

What you’ll do

Act as the technical owner for energy modules and the associated optimization tools
Develop and maintain algorithms for prioritization and sequencing logic in global factory planning
Build advanced optimization algorithms that balance production constraints with demand patterns
Collaborate with demand planning and production planning teams to automate their processes
Work with operations teams to support planning-based tasks at the factory, warehouse, and operation center level
Design and optimize data models that enable high-performance planning operations
Develop efficient ETL processes to integrate data from Tesla’s in-house ERP system and other sources
Write complex SQL queries to analyze supply-demand dynamics and surface planning opportunities
Support executive reporting by creating data pipelines that turn complex planning data into actionable insights

What you’ll bring

A degree in Computer Science, Engineering, Information Science, Operations Research, or a related field, or equivalent experience
2+ years of experience in Software Development or Data Engineering roles
Advanced Python skills with numerical computing libraries such as NumPy, Pandas, and SciPy
Strong SQL proficiency for complex data manipulation and analysis
Experience applying optimization frameworks and algorithms (linear programming, constraint satisfaction)
Understanding of manufacturing planning concepts and S&P processes
Ability to translate complex business requirements into technical specifications
Experience partnering with cross-functional teams and building organic support for technical initiatives
Excellent judgment and a proactive problem-solving mindset
Self-motivation, strong work ethic, and comfort with a rapid pace of change

Technology focus

Python, NumPy, Pandas, SciPy, SQL, linear programming, constraint satisfaction

Benefits at Tesla

Medical plans with $0 payroll deduction
Family-building benefits including fertility, adoption, and surrogacy
Dental (including orthodontic coverage) and vision plans with $0 paycheck contribution
Company paid HSA contribution when enrolled in the High-Deductible medical plan with HSA
Healthcare and Dependent Care Flexible Spending Accounts (FSA)
401(k) with employer match
Employee Stock Purchase Plans
Company paid Basic Life and AD&D
Short-term and long-term disability insurance with a 90 day waiting period
Employee Assistance Program
Sick and Vacation time (Flex time for salary positions, accrued hours for hourly positions) and Paid Holidays
Back-up childcare and parenting support resources
Voluntary benefits including critical illness, hospital indemnity, accident insurance, theft & legal services, and pet insurance
Weight Loss and Tobacco Cessation Programs
Teslas Babies program
Commuter benefits
Employee discounts and perks program
Along with competitive pay, as a full-time Tesla employee, you are eligible for the following benefits at day 1 of hire

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20d ago

Data Analyst

Apple Austin, TX

Austin, TX

20d ago

Full time Analytics Artificial Intelligence Bi Tools

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Job Description

Data Analyst opportunity in the Satellite Connectivity Group at Apple, based in Austin, TX (onsite).

Responsibilities

Collaborate with cross-functional teams to understand the system end-to-end, analyze key metrics, and address questions about performance and user experience.
Mine and synthesize data from multiple sources, using statistical methods and machine learning to identify trends, anomalies, and actionable insights.
Build and maintain data pipelines that enable reliable, repeatable analysis.
Create visualizations, dashboards, and reports that clearly communicate results to both technical and non-technical audiences.
Convert complex findings into simple, compelling narratives that motivate action and drive improvements.
Investigate anomalies and performance issues to determine root causes and recommend solutions.

Requirements

Minimum: 3+ years of experience with data analysis and reporting.
Minimum: Experience synthesizing complex data sources into clear, insightful presentations with an emphasis on the story.
Minimum: Demonstrated experience building analytic tools and analyzing operational data, then distilling results into actionable recommendations.
Minimum: Solid statistical concepts and machine learning algorithm knowledge.
Minimum: Excellent problem-solving skills and ability to work independently.
Minimum: Creativity and willingness to explore new solutions and ideas.
Minimum: Excellent data visualization skills.
Minimum: Proficiency with scripting languages such as Python, R, or MATLAB.
Minimum: Experience with databases and query languages such as SQL.
Minimum: Comfortable working across multiple languages and tools.
Minimum: Excellent written and verbal communication skills, with demonstrated teamwork and leadership skills.
Education: BS or MS in a quantitative field.
Quantitative fields include: data science, statistics, applied mathematics, operations research, engineering, or a related discipline.
Preferred: Familiarity with using AI to improve efficiency.
Preferred: Experience with BI and visualization tools.

Tech Stack

Python, R, MATLAB
SQL
BI and visualization tools
Machine learning, AI

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20d ago

Machine Learning Engineer- Senior Consultant Level

Visa Technology and Operations LLC Austin, TX

Austin, TX

20d ago

$173k - $277k/yr Full time Python Senior Artificial Intelligence

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Job Description

Join Visa Technology and Operations LLC to design and deliver machine learning systems that improve performance, accuracy, and data management.

Responsibilities

Develop and program integrated software algorithms for product and systems applications in structured and unstructured environments
Use machine language and statistical modeling techniques to enhance performance, quality, data management, and accuracy
Perform rigorous validation and detect logical flaws using established machine learning practices
Translate algorithms and technical specifications into production code using current programming languages and technologies
Design and implement adaptive learning approaches, including model validation and A/B testing
Implement explainability methods to support understanding of model decisions

Requirements

8+ years of relevant work experience with a Bachelor Degree, or 5+ years with an Advanced Degree (e.g., Masters, MBA, JD, MD), or 2+ years with a PhD
Experience developing and programming integrated software algorithms for structured and unstructured data environments
Ability to program in one or more scripting languages such as Rust or Python, and one or more programming languages such as Java, C++, or C#
Advanced Generative AI experience/usage

Technologies

Rust, Python, Java, C++, C#, ChatGPT, Microsoft Copilot
TensorFlow, SAS, R, KNIME, Matlab
Generative AI tools
Decision trees, logistic regression, Bayesian analysis, Naïve Bayes, SVM, neural networks

Preferred Qualifications

9+ years relevant work experience with a Bachelor Degree, or 7+ years with an Advanced Degree, or 3+ years with a PhD
Bachelor’s Degree in Computer Science, Operations Research, Statistics, or a highly quantitative field (or equivalent experience) with strength in Deep Learning, Machine Learning, Data Mining, and statistical or mathematical analysis
Experience applying statistical modeling techniques such as decision trees, logistic regression, Bayesian analysis, and others
Experience conducting rigorous validation and identifying logical flaws in machine learning solutions
Experience translating algorithms and technical specifications into code using current programming languages and technologies
Experience designing and implementing adaptive learning methods, model validation, and A/B testing
Experience explaining model decisions and ensuring post-deployment integrity and accuracy
Experience working with large datasets and modern big data and ML/AI technologies
Experience with relevant coursework in modeling techniques such as logistic regression, Naïve Bayes, SVM, decision trees, or neural networks
Experience with one or more statistical tools such as SAS, R, KNIME, or Matlab
Deep learning experience with TensorFlow (plus)

Benefits

Medical, Dental, Vision
401(k)
FSA/HSA
Life Insurance
Paid Time Off
Wellness Program

Location and Work Details

Austin, TX
Onsite
Travel: 5–10%
Work hours: varies based on department needs
Work setting: office setting
Physical/mental requirements: sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment (telephones, computers)

U.S. Applicant Information

Estimated salary range: $173,000.00 to $276,900.00 USD per year (may include potential sales incentive payments, if applicable)
Salary may vary based on job-related factors including knowledge, skills, experience, and location
May be eligible for bonus and equity

Minimum Education

Bachelor Degree (or Advanced Degree/PhD equivalent)

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20d ago

Machine Learning Engineer

Neuralink Austin, TX

Austin, TX

20d ago

$199k - $331k/yr Full time Artificial Intelligence Data Analytics Data Processing

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Job Description

Neuralink is hiring a Machine Learning Engineer to build real-time machine learning and signal processing for brain-computer interfaces in Austin, TX (onsite).

Location: Austin, TX (onsite)
Salary: USD 199,000 - 331,000 per year
Education: Bachelor’s degree in a relevant field

Responsibilities

Develop and iterate on models that decode neural data for BCI use cases
Enable reliable typing for people with paralysis at 35 words per minute and support robotics arm control for activities of daily living
Define research questions that guide development of neural networks and signal processing algorithms aimed at restoring vision for those affected by blindness
Apply foundational knowledge of neural networks and data science to create model capabilities that serve as the basis for BCI machine learning applications
Lead by example through high standards for how systems are built and operated
Contribute to the hardware roadmap by understanding users and identifying product features with the greatest impact on quality of life

Requirements

Experience writing production-level C/C++/Rust and Python
Proven track record designing, building, and shipping real-time ML products
Strong foundation in signal processing, algorithms, and core software engineering principles
Bachelor’s degree in a relevant field or equivalent experience

Technologies

C
C++
Rust
Python

Benefits

Excellent medical, dental, and vision insurance through a PPO plan
Paid holidays
Commuter benefits
Meals provided
Equity in the form of RSUs (Temporary Employees & Interns excluded)
401(k) plan (Interns initially excluded until they work 1,000 hours)
Parental leave (Temporary Employees & Interns excluded)
Flexible time off (Temporary Employees & Interns excluded)

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20d ago

Machine Learning Engineer

Molex Austin, TX

Austin, TX

20d ago

$170k - $250k/yr Full time Python Artificial Intelligence Azure Gpu Compute

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Job Description

Molex is hiring a Machine Learning Engineer in Austin, TX (onsite) to help reduce reliance on full high-fidelity engineering simulations. This role focuses on building and operationalizing physics-informed surrogate models on Azure Machine Learning, so design teams can predict simulation outcomes from design parameters faster, with uncertainty-aware decisions about when full validation is still needed. The salary range is USD 170,000 - 250,000 per year.

What you’ll build and improve

Design and train surrogate models using neural networks, Gaussian processes, gradient-boosted trees, and GNNs/PINNs on Azure GPU compute (ND/NC series).
Apply physics-informed constraints so model outputs remain physically valid, not just statistically accurate.
Create model uncertainty and confidence scoring to identify which designs require full simulation validation.
Continuously retrain models as new simulation results arrive, improving performance over time.

Deploy, monitor, and benchmark

Deploy and version models using Azure ML endpoints and the model registry.
Monitor models on a rolling basis for drift.
Benchmark surrogate performance against full simulation to support platform-level performance tuning.

What you bring

Extensive hands-on production experience building, training, and deploying ML models (not limited to pretrained API usage).
10+ years building ML for physical or engineering systems, including surrogate modeling, physics-informed ML, or scientific ML.
Strong Python skills with PyTorch or TensorFlow.
Understanding of relevant engineering/physics fundamentals and simulation data formats for your domain.
Experience with Azure Machine Learning or a similar cloud ML platform.
Familiarity with uncertainty quantification, including Bayesian approaches and ensembling.

Additional advantages

Direct experience with industry-standard EM or physics simulation tools.
Background in geometric deep learning (graph neural networks and mesh-based models) for CAD data.
Experience in RF/high-speed electronics or interconnect design.

Benefits

Medical, dental, and vision
Flexible spending and health savings accounts
Life insurance
ADD, disability
Retirement
Paid vacation/time off
Educational assistance
May also include infertility assistance
Paid parental leave and adoption assistance

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20d ago

Staff Machine Learning Engineer

PayPal Austin, TX

Austin, TX

20d ago

$179k - $265k/yr Full time Ai Ml Artificial Intelligence Cloud

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Job Description

Join a hybrid team in Austin to lead end to end work on advanced machine learning models, from development through production deployment.

Responsibilities

Drive the design, development, and optimization of advanced machine learning models and algorithms
Oversee preprocessing and analysis for large-scale datasets
Deploy and maintain machine learning solutions in production environments
Partner with data scientists, software engineers, and product teams to integrate ML models into products and services
Monitor deployed model performance, evaluate results, and apply adjustments as needed

Requirements

5+ years of relevant experience and a Bachelor’s degree OR an equivalent combination of education and experience
Strong experience with major ML frameworks including TensorFlow, PyTorch, and scikit-learn
Expertise with cloud platforms and tooling for data processing and model deployment on AWS, Azure, and GCP

Tech Stack

TensorFlow
PyTorch
scikit-learn
AWS
Azure
GCP

Compensation and Location

Austin, Texas (Hybrid) | $178,500 - $265,100 per year
San Jose, California (Primary location) | $196,500 - $291,500 per year
Travel: 0%

Benefits

Comprehensive, choice-based programs supporting personal wellbeing across physical, emotional, and financial health
Generous paid time off
Healthcare coverage for you and your family
Resources to create financial security
Support for your mental health