ZipRecruiter

Log In

1

Ai Algorithm Engineer Jobs in Baton Rouge, LA (NOW HIRING)

TechPossible

AI/ML Engineer

Denham Springs, LA · On-site

$110K - $125K/yr

Keep up with rapidly evolving technologies, algorithms, and industry trends * Work closely with business managers and other engineers to align AI strategies with company goals Required Qualifications:

DataAnnotation

SDLC Engineer - AI Trainer

Baton Rouge, LA · Remote

$50 - $100/hr

... AI models to take on programming tasks that include creating and solving challenging coding ... Experience with algorithms, data structures, and debugging workflows * A current, in progress, or ...

DataAnnotation

QA Engineer - AI Trainer

Baton Rouge, LA · Remote

$50 - $100/hr

... AI models to take on programming tasks that include creating and solving challenging coding ... Experience with algorithms, data structures, and debugging workflows * A current, in progress, or ...

next page

Showing results 1-20

All JobsAi Algorithm Engineer JobsAi Algorithm Engineer Jobs in Baton Rouge, LA

Ai Algorithm Engineer information

See Baton Rouge, LA salary details

$57.1K

$107.2K

$194.9K

How much do ai algorithm engineer jobs pay per year?

As of Jul 11, 2026, the average yearly pay for ai algorithm engineer in Baton Rouge, LA is $107,193.00, according to ZipRecruiter salary data. Most workers in this role earn between $77,300.00 and $127,200.00 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, and why are they important?

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 are AI Algorithm Engineers?

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.
Ai Algorithm Engineer jobs near you

AI/ML Engineer

TechPossible

Denham Springs, LA • On-site

$110K - $125K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 11 days ago

Job description

Benefits:
  • 401(k) matching
  • Health insurance
  • Opportunity for advancement
  • Paid time off
  • Training & development

TechPossible is seeking a motivated AI/ML Engineer to join our team! At TechPossible, youll work alongside a group of dedicated professionals who take pride in delivering high-quality IT and managed services. We support businesses in managing, securing, and maintaining their technology systems, and we do it with a strong commitment to honesty, integrity, and doing things the right way. If youre passionate about building innovative solutions and want to make a meaningful impact, youll feel right at home here.
Job Summary: The AI/ML Engineer is the core hands-on builder on the AI team. This person writes the code that makes the AI features work the voice agent prompts, the intent classifiers, the RAG pipelines, the evaluation harnesses, and the integrations that connect AI capabilities to business systems.
Essential Job Responsibilities: (Including but not limited to)
  • Implement AI workflows, including workflow logic, intent classification, entity extraction, and multi-step decision processes
  • Build and tune LLM-powered features using OpenAI, Anthropic, and other APIs including prompt engineering, structured output parsing, and function calling
  • Develop NLP/classification systems for routing
  • Design and run model evaluations: build test sets, measure accuracy/latency/cost, iterate on prompts and model choices
  • Tune confidence thresholds (e.g., 90%/70% auto-vs-human routing) and monitor drift in production
  • Integrate AI and workflows with existing enterprise systems
  • Implement observability for AI systems, including structured logging, prompt and pipeline tracing, and cost attribution per execution
  • Collaborate with cross-functional teams to operationalize and iterate on prompts
  • Contribute to code review, technical design docs, and on-call rotations
  • Delivers responsive and professional customer support by diagnosing and resolving technical issues, communicating clearly with non-technical users, and ensuring timely follow-up to maintain high levels of customer satisfaction
  • Keep up with rapidly evolving technologies, algorithms, and industry trends
  • Work closely with business managers and other engineers to align AI strategies with company goals
Required Qualifications:
  • Strong experience and knowledge in Python and TypeScript
  • Hands-on LLM API experience: Anthropic Claude, OpenAI, at least one other provider; function calling, JSON mode, streaming
  • Prompt engineering as a systematic practice not ad-hoc wordsmithing, but versioned prompts with test sets and regression checks
  • NLP fundamentals: intent classification, NER, embeddings, semantic search (pgvector, Pinecone)
  • Create evaluation approaches that define meaningful success metrics, build test datasets, and track performance against client-specific KPIs.
  • Model selection tradeoffs: when to use GPT-5 vs. Claude Sonnet vs. Haiku, when to fine-tune, when RAG is the right pattern
Voice AI
  • STT/TTS integration: Deepgram Nova/Aura, Whisper, ElevenLabs
  • Real-time streaming audio handling latency budgets, interruption handling, turn-taking
  • Twilio Voice API, SIP trunking concepts, WebRTC awareness
Software Engineering
  • Backend development: REST APIs, async patterns, message queues
  • Databases: SQL (PostgreSQL, SQL Server), basic schema design; vector DB basics
  • Cloud: Azure (AWS/GCP acceptable), containerization (Docker)
  • Git, CI/CD, code review fundamentals
Preferred Skills: (Not Required)
  • MLOps tooling: Langfuse, MLflow, Weights & Biases
  • Familiarity with model adaptation techniques, such as fine-tuning (e.g., LoRA, supervised approaches)
  • Experience with frameworks: LangChain, LlamaIndex, Pydantic AI used judiciously, not as a crutch

Benefits:
  • Health Insurance TechPossible will pay 50% of the employees premium
  • 401k Contribution TechPossible will match employee contribution up to 3%
  • Optional benefits: Dental, Vision, Accident, Critical Illness, Short Term Disability, and Life Insurance.
  • Paid Time Off
  • Paid Holidays
  • Access to Employee Assistance Program
  • Company provided health club membership
  • Travel reimbursement
  • Opportunities for professional development and certification support
  • Supportive, team-oriented work environment

At TechPossible, we speak human, and we deliver results. We embed with your team to take full responsibility for your technology, bringing clarity where theres complexity and control where theres risk. Our experts secure, optimize, and manage your systems so they consistently perform at a high level. We dont just keep things running; we make your technology a reliable driver of growth and a foundation for whats next.