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Ai Algorithm Engineer Jobs in Dallas, TX (NOW HIRING)

The Gen AI Solution Engineer role involves leveraging generative AI technologies to build scalable ... refine algorithms to meet business needs. • Review plan for smooth deployment into scalable ...

AI Engineer

Dallas, TX · On-site

$50K - $112K/yr

Within our Internal Firm Services practice, you will apply data, algorithms, and software ... AI engineering What You Must Have - At least a Bachelor's degree or, in lieu of a degree ...

AI Engineer

Fort Worth, TX · On-site

$50K - $112K/yr

Within our Internal Firm Services practice, you will apply data, algorithms, and software ... AI engineering What You Must Have - At least a Bachelor's degree or, in lieu of a degree ...

Basic understanding of web development, debugging, data structures, algorithms, and software ... Grow in AI and Engineering: Work closely with experienced engineers and technical leaders while ...

AI Engineer

Dallas, TX · On-site

$55K - $187K/yr

... AI Engineer, you will be at the forefront of transforming raw data into actionable insights ... Within our Internal Firm Services practice, you will apply data, algorithms, and software ...

AI Engineer

Fort Worth, TX · On-site

$55K - $187K/yr

... AI Engineer, you will be at the forefront of transforming raw data into actionable insights ... Within our Internal Firm Services practice, you will apply data, algorithms, and software ...

Sr. Engineer, AI & ML

Dallas, TX · On-site

$103K - $142K/yr

... Engineer, Artificial Intelligence is a technologist with domain-specific expertise in Generative AI ... Data Science Libraries and Algorithms (TensorFlow, Scikit, PyTorch, etc) Work Location and ...

Showing results 41-60

Ai Algorithm Engineer information

See Dallas, TX salary details

$58.9K

$110.4K

$200.8K

How much do ai algorithm engineer jobs pay per year?

As of Aug 6, 2026, the average yearly pay for ai algorithm engineer in Dallas, TX is $110,430.00, according to ZipRecruiter salary data. Most workers in this role earn between $79,600.00 and $131,100.00 per year, depending on experience, location, and employer.

What are some common challenges AI algorithm engineers face when deploying models to production environments?

AI Algorithm Engineers often encounter challenges such as ensuring model scalability, maintaining inference speed, and handling the integration of models with existing systems. Additionally, they must address issues like model drift, data pipeline inconsistencies, and the need for continuous monitoring to maintain accuracy over time. Effective collaboration with data engineers, software developers, and DevOps teams is essential for successful deployment and ongoing model performance.

What is the difference between Ai Algorithm Engineer vs Data Scientist?

AspectAi Algorithm EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; knowledge of algorithms and programmingBachelor's or Master's in CS, Statistics, or related fields; strong analytical skills
Work EnvironmentDevelops and optimizes AI algorithms, often in R&D or product teamsAnalyzes data, builds models, and provides insights for business decisions
Industry UsageTech companies, AI startups, research institutionsFinance, healthcare, marketing, tech firms

While both roles require strong technical skills and a background in data or algorithms, Ai Algorithm Engineers focus on designing and improving AI algorithms, whereas Data Scientists analyze data to generate insights and build predictive models. The roles often overlap but serve different primary functions within organizations.

What are the key skills and qualifications needed to thrive as an AI algorithm engineer?

To thrive as an AI Algorithm Engineer, you need strong expertise in mathematics, programming (especially Python, C++, or Java), and a solid background in computer science or a related field, often supported by a relevant degree. Familiarity with machine learning frameworks (like TensorFlow, PyTorch), data processing tools, and sometimes certifications in AI or data science are typically required. Creative problem-solving, strong analytical thinking, and effective communication are crucial soft skills that set top candidates apart. These skills and qualifications are essential for designing robust AI solutions, collaborating with cross-functional teams, and driving innovation in rapidly evolving technical environments.

What is an AI algorithm engineer?

AI Algorithm Engineers are professionals who design, develop, and optimize algorithms that enable artificial intelligence systems to learn from data and perform complex tasks. They work with machine learning, deep learning, and other AI techniques to create models that can analyze information, make predictions, or automate processes. AI Algorithm Engineers often collaborate with data scientists and software developers to implement and improve AI solutions for various industries, such as healthcare, finance, and technology. Their work involves both theoretical research and practical application, requiring strong programming and mathematical skills.
What are popular job titles related to Ai Algorithm Engineer jobs in Dallas, TX? For Ai Algorithm Engineer jobs in Dallas, TX, the most frequently searched job titles are:
What job categories do people searching Ai Algorithm Engineer jobs in Dallas, TX look for? The top searched job categories for Ai Algorithm Engineer jobs in Dallas, TX are:
What cities near Dallas, TX are hiring for Ai Algorithm Engineer jobs? Cities near Dallas, TX with the most Ai Algorithm Engineer job openings:

Gen AI Solution Engineer

Infosys

Dallas, TX • On-site

Full-time

Posted 28 days ago


Infosys rating

7.0

Company rating: 7.0 out of 10

Based on 62 frontline employees who took The Breakroom Quiz

149th of 221 rated it services


Job description

Job Summary:
Infosys is a global leader in next-generation digital services and consulting, enabling clients worldwide to navigate digital transformation. The Gen AI Solution Engineer role involves leveraging generative AI technologies to build scalable, production-ready AI and analytics solutions, collaborating with cross-functional teams, and driving innovation in AI applications. The position focuses on advanced modeling, AI governance, and mentoring team members to align analytics with business goals.
Responsibilities:
• Review data preparation tasks, and plans to address patterns or anomalies, while ensuring data readiness for advanced modeling and AI.
• Review models for complex use cases (e.g., forecasting models, LLM-based solutions), and refine algorithms to meet business needs.
• Review plan for smooth deployment into scalable, production-ready solutions.
• Review test plans and test results for analytics use cases, while defining optimization standards for model accuracy and stability, in alignment with business goals.
• Build models and analytics solutions tailored to business needs.
• Ensure quality and scalability across client engagements while actively contributing to knowledge assets and innovation streams.
• Leverage tools like SAS and R/Python to create reusable customizations for non-ML, ML, and deep learning algorithms, while enhancing analytics including LLMs, and create innovative, cost-effective solutions.
• Review and refine analytics problems; identify data sources and extract from diverse environments.
• Oversee analysis execution and drive business insights.
• Create monitoring strategies across multiple projects, embedding governance frameworks to ensure robustness, reliability, and risk awareness.
• Review monitoring frameworks, refine documentation/reporting templates, and present insights on anomalies or slippages to stakeholders.
• Refine documentation strategy across teams, ensuring transparency and reproducibility of complex analytics solutions.
• Collaborate with cross-functional teams, ensuring alignment between analytics delivery and business strategy.
• Review analytics outputs for adherence to quality frameworks and project commitments.
• Recommend improvements to quality metrics and guide team members to align with standards.
• Identify and recommend model changes needed for successful deployment.
• Engage in creation and refinement of IP assets such as analytics prototypes and accelerators.
• Develop insights, whitepapers, and proof-of-concept summaries that highlight innovative thinking.
• Review innovative models and applications in non-ML, ML, deep learning, or LLM areas.
• Support participation in forums and internal knowledge exchanges.
• Deliver training sessions on technical and analytics-specific topics.
• Collaborate on content creation and mentor team members through hands- on guidance in live projects.
• Provide input for segment and unit-level business plans.
Qualifications:
Required:
• Enterprise GenAI and Agentic AI solutions across RAG, AI agents, conversational AI, enterprise search, workflow automation, document intelligence, and AI copilots; comfortable with planner-executor, reflection, multi-agent, and graph-based orchestration patterns.
• Hands-on with orchestration frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, CrewAI) and vector databases (Pinecone, Weaviate, Milvus, pgvector, FAISS, ChromaDB, Azure AI Search); working knowledge of grounding, prompt engineering, and context management.
• Experience integrating GenAI with Azure OpenAI, AWS Bedrock, Vertex AI, OpenAI, Anthropic, and Gemini, along with enterprise APIs, middleware, and data platforms.
• Command of AI governance, LLMOps, evaluation, observability, guardrails, model safety, compliance, and cloud-native deployment.
• Ability to define reference architectures, lead solutioning discussions, drive architecture reviews, and collaborate with enterprise architects, business stakeholders, and engineering teams.
• Bachelor’s degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education.
• This position may require relocation and/or travel to work/project location.
• Candidates authorized to work for any employer in the United States without employer-based visa sponsorship are welcome to apply. Infosys is unable to provide immigration sponsorship for this role now or in the future.
Preferred:
• Exposure to open-source LLM ecosystems — Hugging Face, PyTorch, LoRA, QLoRA, PEFT — and models such as Llama, Mistral, Gemma, DeepSeek, and Falcon.
• Familiarity with multimodal AI, including vision-language models, speech and audio models, and image or video generation.
• Familiarity with DevOps and IaC tooling (GitHub Actions, Jenkins, Terraform, Helm, Kubernetes) and awareness of front-end stacks (React, Angular, TypeScript, GraphQL) used in copilot interfaces.
Company:
Infosys is a technology company that offers consulting, outsourcing, cloud infrastructure, program management, and software services. Founded in 1981, the company is headquartered in Bangalore, IND, with a team of 10001+ employees. The company is currently Late Stage.

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