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based on 221 Reviews

1 Mindfire Solutions Job

Lead Engineer - AI/ML

Mindfire Solutions

based on 221 Reviews

2-6 years

New Delhi

1 vacancy

Lead Engineer - AI/ML

Mindfire Solutions

posted 5mon ago

Flexible timing

Key skills for the job

+ 4 more

Client Interaction: Discuss client requirements and develop proposals tailored to their needs.
Demonstrations and Workshops: Conduct solution/product demonstrations, POC/Proof of Technology workshops, and prepare effort estimates in line with customer budgets and organizational financial guidelines.
Model Oversight: Oversee the development and deployment of AI models, especially those generating content such as text, images, or other media.
AI Solutions: Engage in coding, designing, developing, implementing, and deploying advanced AI solutions.
Expertise Utilization: Utilize your expertise in NLP, Python programming, LLMs, Deep Learning, and AI principles to drive the development of transformative technologies.
Leadership and Initiative: Actively lead projects and contribute to both unit-level and organizational initiatives to provide high-quality, value-adding solutions to customers.
Strategic Development: Develop value-creating strategies and models to help clients innovate, drive growth, and increase profitability.
Technology Awareness: Stay informed about the latest technologies and industry trends.
Problem-Solving and Collaboration: Employ logical thinking and problem-solving skills, and collaborate effectively.
Client Interfacing: Demonstrate strong client interfacing skills.
Project and Team Management: Manage projects and teams efficiently.

Skills: Hands-on expertise in NLP, Computer Vision, programming, and related concepts.
Leadership: Capable of leading and mentoring a team of AI engineers and researchers, setting strategies for AI model development and deployment, and ensuring these align with business goals.
Technical Proficiency: Proficient in implementing and optimizing advanced AI solutions using Deep Learning and NLP, with tools such as TensorFlow, PyTorch, Spark, and Keras.
LLM Experience: Experience with Large language Models like GPT 3.5, GPT 4, Llama, Gemini, Mistral, etc. along with experience in LLM integration frameworks like LangChain, Llamaindex, AgentGPT, etc.
Deep Learning OCR: Extensive experience implementing solutions using Deep Learning OCR algorithms.
Neural Networks: Working knowledge of Artificial Neural Networks (ANNs), Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Adversarial Networks (GANs).
Python Expertise: Strong coding skills in Python, including related frameworks, best practices, and design patterns.
Preferred Knowledge: Familiarity with word embeddings, transformer models, and image/text generation and processing.
Deployment: Experience deploying AI/ML solutions as a service or REST API endpoints on Cloud or Kubernetes.
Development Methodologies: Proficient in development methodologies and writing unit tests in Python.
Cloud: Knowledge of cloud computing platforms and services, such as AWS, Azure, or Google Cloud.