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- Minimum of (2+) years of experience in AI-based application development.
- Fine-tune pre-existing models to improve performance and accuracy.
- Experience with TensorFlow or PyTorch, Scikit-learn, or similar ML frameworks and familiarity with APIs like OpenAI or vertex AI
- Experience with NLP tools and libraries (e.g., NLTK, SpaCy, GPT, BERT).
- Implement frameworks like LangChain, Anthropics Constitutional AI, OpenAIs, Hugging Face, and Prompt Engineering techniques to build robust and scalable AI applications.
- Evaluate and analyze RAG solution and Utilise the best-in-class LLM to define customer experience solutions (Fine tune Large Language models (LLM)).
- Architect and develop advanced generative AI solutions leveraging state-of-the-art language models (LLMs) such as GPT, LLaMA, PaLM, BLOOM, and others.
- Strong understanding and experience with open-source multimodal LLM models to customize and create solutions.
- Explore and implement cutting-edge techniques like Few-Shot Learning, Reinforcement Learning, Multi-Task Learning, and Transfer Learning for AI model training and fine-tuning.
- Proficiency in data preprocessing, feature engineering, and data visualization using tools like Pandas, NumPy, and Matplotlib.
- Optimize model performance through experimentation, hyperparameter tuning, and advanced optimization techniques.
- Proficiency in Python with the ability to get hands-on with coding at a deep level.
- Develop and maintain APIs using Python's FastAPI, Flask, or Django for integrating AI capabilities into various systems.
- Ability to write optimized and high-performing scripts on relational databases (e.g., MySQL, PostgreSQL) or non-relational database (e.g., MongoDB or Cassandra)
- Enthusiasm for continuous learning and professional developement in AI and leated technologies.
- Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
- Knowledge of cloud services like AWS, Google Cloud, or Azure.
- Proficiency with version control systems, especially Git.
- Familiarity with data pre-processing techniques and pipeline development for Al model training.
- Experience with deploying models using Docker, Kubernetes
- Experience with AWS Bedrock, and Sagemaker is a plus
- Strong problem-solving skills with the ability to translate complex business problems into Al solutions.



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.


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.



- 3+ years of Experience majoring in applying AI/ML/ NLP / deep learning / data-driven statistical analysis & modelling solutions.
- Programming skills in Python, knowledge in Statistics.
- Hands-on experience developing supervised and unsupervised machine learning algorithms (regression, decision trees/random forest, neural networks, feature selection/reduction, clustering, parameter tuning, etc.). Familiarity with reinforcement learning is highly desirable.
- Experience in the financial domain and familiarity with financial models are highly desirable.
- Experience in image processing and computer vision.
- Experience working with building data pipelines.
- Good understanding of Data preparation, Model planning, Model training, Model validation, Model deployment and performance tuning.
- Should have hands on experience with some of these methods: Regression, Decision Trees,CART, Random Forest, Boosting, Evolutionary Programming, Neural Networks, Support Vector Machines, Ensemble Methods, Association Rules, Principal Component Analysis, Clustering, ArtificiAl Intelligence
- Should have experience in using larger data sets using Postgres Database.


Location: Ahmedabad / Pune
Team: Technology
Company Profile
InFoCusp is a company working in the broad field of Computer Science, Software Engineering, and Artificial Intelligence (AI). It is headquartered in Ahmedabad, India, having a branch office in Pune.
We have worked on / are working on AI projects / algorithms-heavy projects with applications ranging in finance, healthcare, e-commerce, legal, HR/recruiting, pharmaceutical, leisure sports and computer gaming domains. All of this is based on the core concepts of data science,
computer vision, machine learning (with emphasis on deep learning), cloud computing, biomedical signal processing, text and natural language processing, distributed systems, embedded systems and the Internet of Things.
PRIMARY RESPONSIBILITIES:
● Applying machine learning, deep learning, and signal processing on large datasets (Audio, sensors, images, videos, text) to develop models.
● Architecting large scale data analytics/modeling systems.
● Designing and programming machine learning methods and integrating them into our ML framework/pipeline.
● Analyzing data collected from various sources,
● Evaluate and validate the analysis with statistical methods. Also presenting this in a lucid form to people not familiar with the domain of data science/computer science.
● Writing specifications for algorithms, reports on data analysis, and documentation of algorithms.
● Evaluating new machine learning methods and adapting them for our
purposes.
● Feature engineering to add new features that improve model
performance.
KNOWLEDGE AND SKILL REQUIREMENTS:
● Background and knowledge of recent advances in machine learning, deep learning, natural language processing, and/or image/signal/video processing with at least 3 years of professional work experience working on real-world data.
● Strong programming background, e.g. Python, C/C++, R, Java, and knowledge of software engineering concepts (OOP, design patterns).
● Knowledge of machine learning libraries Tensorflow, Jax, Keras, scikit-learn, pyTorch. Excellent mathematical skills and background, e.g. accuracy, significance tests, visualization, advanced probability concepts
● Ability to perform both independent and collaborative research.
● Excellent written and spoken communication skills.
● A proven ability to work in a cross-discipline environment in defined time frames. Knowledge and experience of deploying large-scale systems using distributed and cloud-based systems (Hadoop, Spark, Amazon EC2, Dataflow) is a big plus.
● Knowledge of systems engineering is a big plus.
● Some experience in project management and mentoring is also a big plus.
EDUCATION:
- B.E.\B. Tech\B.S. candidates' entries with significant prior experience in the aforementioned fields will be considered.
- M.E.\M.S.\M. Tech\PhD preferably in fields related to Computer Science with experience in machine learning, image and signal processing, or statistics preferred.