Tecblic Private LImited

Job opening for Business Development Executives

Looking for a place to showcase your skills and take steps to success? Then this is the position you are looking for. Tecblic is one of the fastest-growing IT companies in Ahmedabad. We believe in providing a healthy work culture. Exposure to working with international customers in the USA, UK, Europe, Australia, or Middle East countries will be an added advantage

Location: Ahmedabad 

Experience: 3 to 4 years

The ideal candidate should have experience in International Sales and also in all stages of the sales cycle. They should be confident in building new clients and maintaining the existing ones. They should have evidence of strong communication skills and possess good negotiating abilities.

Job Responsibilities: 

-Manage sales pipeline 

-Analyse the market and establish competitively 

-Track metrics to ensure that targets are hit. 

-Creating proposals, presentations, and other relevant collateral 

-Preparing PowerPoint presentations and sales displays 

-Experienced in Bidding portal 

-Experience in Enterprise Sales will be an advantage

Come! Join our team, we will provide you with the best that we can.

Job Description: Machine Learning Engineer – LLM and Agentic AI

Location: Ahmedabad

Experience: 4+ years

Employment Type: Full-Time

________________________________________

About Us

Join a forward-thinking team at Tecblic, where innovation meets cutting-edge technology. We specialize in delivering AI-driven solutions that empower businesses to thrive in the digital age. If you're passionate about LLMs, machine learning, and pushing the boundaries of Agentic AI, we’d love to have you on board.

________________________________________

Key Responsibilities

• Research and Development: Research, design, and fine-tune machine learning models, with a focus on Large Language Models (LLMs) and Agentic AI systems.

• Model Optimization: Fine-tune and optimize pre-trained LLMs for domain-specific use cases, ensuring scalability and performance.

• Integration: Collaborate with software engineers and product teams to integrate AI models into customer-facing applications and platforms.

• Data Engineering: Perform data preprocessing, pipeline creation, feature engineering, and exploratory data analysis (EDA) to prepare datasets for training and evaluation.

• Production Deployment: Design and implement robust model deployment pipelines, including monitoring and managing model performance in production.

• Experimentation: Prototype innovative solutions leveraging cutting-edge techniques like reinforcement learning, few-shot learning, and generative AI.

• Technical Mentorship: Mentor junior team members on best practices in machine learning and software engineering.

________________________________________

Requirements

Core Technical Skills:

• Proficiency in Python for machine learning and data science tasks.

• Expertise in ML frameworks and libraries like PyTorch, TensorFlow, Hugging Face, Scikit-learn, or similar.

• Solid understanding of Large Language Models (LLMs) such as GPT, T5, BERT, or Bloom, including fine-tuning techniques.

• Experience working on NLP tasks such as text classification, entity recognition, summarization, or question answering.

• Knowledge of deep learning architectures, such as transformers, RNNs, and CNNs.

• Strong skills in data manipulation using tools like Pandas, NumPy, and SQL.

• Familiarity with cloud services like AWS, GCP, or Azure, and experience deploying ML models using tools like Docker, Kubernetes, or serverless functions.

Additional Skills (Good to Have):

• Exposure to Agentic AI (e.g., autonomous agents, decision-making systems) and practical implementation.

• Understanding of MLOps tools (e.g., MLflow, Kubeflow) to streamline workflows and ensure production reliability.

• Experience with generative AI models (GANs, VAEs) and reinforcement learning techniques.

• Hands-on experience in prompt engineering and few-shot/fine-tuned approaches for LLMs.

• Familiarity with vector databases like Pinecone, Weaviate, or FAISS for efficient model retrieval.

• Version control (Git) and familiarity with collaborative development practices.

General Skills:

• Strong analytical and mathematical background, including proficiency in linear algebra, statistics, and probability.

• Solid understanding of algorithms and data structures to solve complex ML problems.

• Ability to handle and process large datasets using distributed frameworks like Apache Spark or Dask (optional but useful).

________________________________________

Soft Skills:

• Excellent problem-solving and critical-thinking abilities.

• Strong communication and collaboration skills to work with cross-functional teams.

• Self-motivated, with a continuous learning mindset to keep up with emerging technologies.