UX Designer

Job Description: Machine Learning Engineer – LLM and Agentic AI

Location: Ahmedabad

Experience: 4+ years

Employment Type: Full-Time

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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.

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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.

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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).

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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.

Role Overview:

We are seeking a highly skilled and motivated Data Scientist to join our growing team. The ideal candidate will be responsible for developing and deploying machine learning models from scratch to production level, focusing on building robust data-driven products. You will work closely with software engineers, product managers, and other stakeholders to ensure our AI-driven solutions meet the needs of our users and align with the company's strategic goals.

Key Responsibilities:

• Develop, implement, and optimize machine learning models and algorithms to support product development.
• Work on the end-to-end lifecycle of data science projects, including data collection, preprocessing, model training, evaluation, and deployment.
• Collaborate with cross-functional teams to define data requirements and product taxonomy.
• Design and build scalable data pipelines and systems to support real-time data processing and analysis.
• Ensure the accuracy and quality of data used for modeling and analytics.
• Monitor and evaluate the performance of deployed models, making necessary adjustments to maintain optimal results.
• Implement best practices for data governance, privacy, and security.
• Document processes, methodologies, and technical solutions to maintain transparency and reproducibility.

Qualifications:

• Bachelor's or Master's degree in Data Science, Computer Science, Engineering, or a related field.
• 5+ years of experience in data science, machine learning, or a related field, with a track record of developing and deploying products from scratch to production.
• Strong programming skills in Python and experience with data analysis and machine learning libraries (e.g., Pandas, NumPy, TensorFlow, PyTorch).
• Experience with cloud platforms (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker).
• Proficiency in building and optimizing data pipelines, ETL processes, and data storage solutions.
• Hands-on experience with data visualization tools and techniques.
• Strong understanding of statistics, data analysis, and machine learning concepts.
• Excellent problem-solving skills and attention to detail.
• Ability to work collaboratively in a fast-paced, dynamic environment.

Preferred Qualifications:

• Knowledge of microservices architecture and RESTful APIs.
• Familiarity with Agile development methodologies.
• Experience in building taxonomy for data products.
• Strong communication skills and the ability to explain complex technical concepts to non-technical stakeholders.

Selected candidate's day-to-day responsibilities include:

1. Speaking to parents (leads given by us) and:

   1. Convincing them to book a consultation (paid or free, as applicable)

   2. Upselling/converting to paid subscriptions/courses and programs, wherever applicable

2. Communicating with prospects via email and whatsapp
3. Creating and maintaining MIS and daily reports

Role - Manager Programmatic

About our client :

Our Client is a digital- first global performance marketing agency& world's largest media investment company which is a part of WPP. They a global digital transformation agency with 1200 employees across 21 nations. Our team of experts support clients in programmatic, social, paid search, analytics, technology, organic search, affiliate marketing, e-commerce and across traditional channels.

Locations - Mumbai, Pune & Chennai

What your day job looks like :

- Manage a team of programmatic professionals with expertise in programmatic media

- Maintain positive client relationships, expectations, and communications

- Identify and solve client risks before they escalate to issues

- Oversee the cross-functional campaign development with internal SEO/Search/Content/Social teams as well as sister media agencies

- Build on existing level of programmatic expertise and develop a reputation for innovation and efficiency internally

- Ensure the integration of programmatic into the overall communications strategy

- Support and lead the strategic development and execution of programmatic campaigns

- Foster teamwork and create a constructive work environment

- Maintain a high level of employee commitment

- Provide team leadership that rewards creativity

- Demonstrate thought leadership for clients and the industry

- Educate clients on the importance of programmatic in the overall marketing mix

- Understand clients' business and generate new ideas to enhance client performance

- Provide effective analysis to support marketing recommendations.

What you'll bring:

- 4+ years of aligned industry experience, preferably within an agency

- Experience executing on Programmatic platforms (DV360, The Trade Desk, App Nexus (Xandr Invest), Amazon, etc.)

- Experience with analytical tools is an asset (Google Analytics, PMP Partners, Ad Servers, DMPs, etc.)

- Demonstrated strong client relationship responsibility

- Proven account management experience, including analytical and creative problem-solving skills

- Ability to interact in a professional manner and communicate with clients over calls

- Proven ability to lead successful campaigns

- Superior verbal and written skills with outstanding presentation ability

- High level of attention to detail and the ability to handle and prioritize multiple accounts

- High level of technical proficiency in Microsoft Office, specifically Excel and PowerPoint

- Come with experience of handling 6-7 direct reporters

• Support the entire application lifecycle (concept, design, test, release, and support)
• Produce fully functional mobile applications writing clean code from designs and wireframes
• Write unit and UI tests to identify malfunctions
• Troubleshoot and debug to optimize performance
• Design interfaces to improve user experience
• Stay up-to-date with new technology trends

• Proven work experience as a Mobile developer
• Demonstrable portfolio of released applications on the App Store or the Android market
• In-depth knowledge of programming in React Native.
• Experience with Javascript libraries.
• Experience with third-party libraries and APIs
• Familiarity with OOP design principles
• Excellent analytical skills with a good problem-solving attitude
• Ability to perform in a team environment
• Understanding of REST principles

DeepSource is working on building tools that help developers ship good code. There are over 40 million developers in the world, and all of them write and review code in some form. There’s a massive opportunity to impact how software is built right from where the code is written using automation and intelligence, that not only improves developer productivity but also increases software’s robustness.

The Language Engineering team works on the source code analyzers, including both programming languages and configuration-as-code systems. As a member of the Language Engineering team, you will work on building the best, most comprehensive, PHP analyzer in the world. You will add new rules and Autofixes for finding more issues with code and automatically fixing them. You will be involved with the community to understand the problems with static analysis tools in the PHP ecosystem.

• Identify bad code practices in PHP and write new rules to detect them.

• Improve the coverage of automatically fixable issues.

• Ensure fewer false positives are reported by the analyzer.

• Work on the internal tools that support analysis runtimes.

• Contribute to open-source static analysis tools.

• Strong foundational knowledge in Computer Science.

• At least 3 years of professional software development experience in PHP.

• Understanding of the nuances of execution of the source code (AST, data flow graphs, etc).

• Familiarity with PHP best practices followed in the industry.

• Native experience with Linux/Unix environment.

• A focus on delivering high-quality code through strong testing practices.

We offer competitive compensation with meaningful stock options, a generous vacation policy, and a workstation of your choice, to name a few of the perks.

JavaScript

- ReactJS

- Redux-Saga

- ES6 (or TypeScript) syntax

- Good problem-solving

- Good debugging

Good to have :

- TypeScript experience

- Material UI experience

- JEST knowledge

- Git and Github/Gitlab/Bitbucket experience

Skill Set:

• Strong knowledge in SQL Server
• Program and develop SQL scripts, tables, views, stored procedures, functions, triggers & constraints.
• Scripting (PowerShell, shell scripting)
• Azure Database (Nice to have)
• Experience with backups, restores and recovery models.
• Familiarity with database design, documentation and coding.

 Responsibilities: 

• Configures and validates database backup routines on a regular basis.
• Establish a regular data retention plan.
• Optimizes database performance through the use of database performance tuning techniques and tools.
• Require extensive familiarity with data management principles and best practices in order to properly store, migrate, and structure data for multiple applications.