Offer summary

Qualifications:

Bachelor’s degree in Computer Science, AI, or a related field., Proficient in Python and machine learning frameworks like TensorFlow and PyTorch., Experience with cloud services and scalable architectures for model deployment., Strong knowledge of LLMs and MLOps practices, with excellent problem-solving skills..

Key responsabilities:

Develop machine learning models and deep learning architectures for various applications.

Build multi-agent systems and AI frameworks to enhance product capabilities.

Fine-tune and optimize large language models using advanced techniques.

Deploy AI models on cloud platforms and ensure they scale efficiently.

Job description

Charger Logistics Inc. is a world- class asset-based carrier with locations across North America. With over 20 years of experience providing the best logistics solutions, Charger Logistics has transformed into a world-class transport provider and continues to grow.

Charger Logistics invests time and support into its employees to provide them with the room to learn and grow their expertise and work their way up. We are entrepreneurial-minded organization that welcomes and support individual ideas and strategies.

We are seeking a talented AI Engineer to design, build, and deploy cutting-edge AI solutions. You'll collaborate with data scientists, engineers, and product teams to create intelligent systems that drive real business impact.

Responsibilities:

Develop machine learning models and deep learning architectures (NLP, computer vision, speech AI).
Build multi-agent systems, LLM-based frameworks, and AI copilots.
Fine-tune and optimize LLMs using techniques like LoRA, PEFT, and RAG.
Deploy AI models on cloud platforms (AWS, GCP, Azure) with Docker and Kubernetes.
Scale AI systems to handle high-volume environments with efficiency.
Stay updated with the latest AI research and incorporate best practices.

Requirements

Bachelor’s in Computer Science, AI, or related field.
Proficient in Python and ML frameworks (TensorFlow, PyTorch).
Experience with cloud services, model deployment, and scalable architectures.
Strong knowledge of LLMs, multi-agent orchestration, and MLOps practices.
Excellent problem-solving and collaboration skills.
Hands-on experience with ASR, TTS, voice applications, or conversational AI is preferred.

Benefits