AI Engineer III

Job Details

• Hybrid: 2-3 days per week in office; local candidates
• Working Hours: 8am - 5pm
• Travel: 20%, mostly domestic, customer sites or conference
• Interview Process: In-person, 3 rounds
• Standard 5-panel drug screen required

Position Summary

An AI (Artificial Intelligence) Engineer develops and trains AI models to automate processes and solve complex problems. They design and implement AI systems, ensuring they function effectively and align with business objectives.

Responsibilities

• Evaluate machine learning processes and select appropriate models.
• Collect and analyze large datasets to train AI models.
• Develop and deploy AI algorithms and systems.
• Collaborate with crossfunctional teams to establish goals for AI processes.
• Test and validate AI models to ensure accuracy and effectiveness.
• Manage data and project infrastructure.
• Stay updated on the latest AI developments and technologies.

Qualifications

• Masters degree in Computer Science, Engineering, or a related field.
• Proven experience as an AI Engineer or in a similar role.
• Strong programming skills in languages such as Python, R, or Java.
• Experience with machine learning frameworks and libraries.
• Excellent analytical and problemsolving abilities.
• Effective communication and collaboration skills.

Additional Skills

• Strong Large Language Model (LLM) Expertise
  Hands-on experience fine-tuning, adapting, and deploying LLMs, including prompt engineering, embeddings, and context management.

• LLM Application & System Architecture
  Proven ability to design and implement production-grade LLM solutions such as RAG pipelines, agents, and tool/function-calling systems.

• Production MLOps & Model Lifecycle Management
  Experience owning the end-to-end ML lifecycle, including CI/CD, deployment, monitoring, versioning, and performance/cost optimization.

• Advanced Python & Software Engineering
  Strong Python skills with experience building scalable, testable APIs and services that integrate ML/LLM models into enterprise systems.

• Cloud-Based Scalable ML Infrastructure
  Hands-on experience with AWS, Azure, or GCP, including containerization (Docker), orchestration (Kubernetes), and GPU-based ML workloads.

Technical Keywords

• advanced python
• CI/CD
• CNNs, RNNs, Transformers
• Docker Container
• Docker Swarm
• Kubernetes
• LLM
• REST, gRPC
• vector database

Shift

• advanced python
• CI/CD
• CNNs, RNNs, Transformers
• Docker Container
• Docker Swarm
• Kubernetes
• LLM
• REST, gRPC
• vector database

EEO Statement

"Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of - Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans."

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Job Details

• Hybrid: 2-3 days per week in office; local candidates
• Working Hours: 8am - 5pm
• Travel: 20%, mostly domestic, customer sites or conference
• Interview Process: In-person, 3 rounds
• Standard 5-panel drug screen required

Position Summary

An AI (Artificial Intelligence) Engineer develops and trains AI models to automate processes and solve complex problems. They design and implement AI systems, ensuring they function effectively and align with business objectives.

Responsibilities

• Evaluate machine learning processes and select appropriate models.
• Collect and analyze large datasets to train AI models.
• Develop and deploy AI algorithms and systems.
• Collaborate with crossfunctional teams to establish goals for AI processes.
• Test and validate AI models to ensure accuracy and effectiveness.
• Manage data and project infrastructure.
• Stay updated on the latest AI developments and technologies.

Qualifications

• Masters degree in Computer Science, Engineering, or a related field.
• Proven experience as an AI Engineer or in a similar role.
• Strong programming skills in languages such as Python, R, or Java.
• Experience with machine learning frameworks and libraries.
• Excellent analytical and problemsolving abilities.
• Effective communication and collaboration skills.

Additional Skills

• Strong Large Language Model (LLM) Expertise
  Hands-on experience fine-tuning, adapting, and deploying LLMs, including prompt engineering, embeddings, and context management.

• LLM Application & System Architecture
  Proven ability to design and implement production-grade LLM solutions such as RAG pipelines, agents, and tool/function-calling systems.

• Production MLOps & Model Lifecycle Management
  Experience owning the end-to-end ML lifecycle, including CI/CD, deployment, monitoring, versioning, and performance/cost optimization.

• Advanced Python & Software Engineering
  Strong Python skills with experience building scalable, testable APIs and services that integrate ML/LLM models into enterprise systems.

• Cloud-Based Scalable ML Infrastructure
  Hands-on experience with AWS, Azure, or GCP, including containerization (Docker), orchestration (Kubernetes), and GPU-based ML workloads.

Technical Keywords

• advanced python
• CI/CD
• CNNs, RNNs, Transformers
• Docker Container
• Docker Swarm
• Kubernetes
• LLM
• REST, gRPC
• vector database

Shift

• advanced python
• CI/CD
• CNNs, RNNs, Transformers
• Docker Container
• Docker Swarm
• Kubernetes
• LLM
• REST, gRPC
• vector database

EEO Statement

"Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of - Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans."