Description :

Job Title : AI Engineer

Location : 100% Remote

Experience : 2-3 Years

Education : Bachelors degree in Computer Science, Information Technology, Data Science, or related technical fields

Employment Type : Full-time, Long-term

Start Date : ASAP

About Us :

AvenDATA (Futuretech Factory One) is driving an AI-first transformation by building intelligent agents, automation models, and advanced decision systems to enhance productivity across the organization.

Our mission is to identify high-impact business use cases, develop tailored AI solutions, and embed them into enterprise workflows to deliver measurable improvements.

We are rapidly expanding our internal AI capability and are looking for talented engineers who can help operationalize AI at scale-through strong discovery, solution design, model development, and deployment expertise.

Role Overview :

We are seeking a highly skilled and motivated AI Engineer with strong hands-on experience in Python, machine learning, and deep learning.

The ideal candidate will have expertise in data preprocessing, model development, cloud deployments, and MLOps practices.

You will play a key role in translating business use cases into scalable AI applications and integrating them into production systems.

This is an excellent opportunity for candidates passionate about building real-world AI products, collaborating with cross-functional teams, and contributing to an ambitious AI transformation initiative.

Key Responsibilities :

AI & Machine Learning Development :

- Design, develop, and deploy machine learning models for a variety of business use cases.

- Build supervised and unsupervised learning solutions, including classification, regression, clustering, and recommendation systems.

- Develop deep learning models (CNNs, RNNs, Transformers) for NLP, vision, and structured data applications.

Data Engineering & Preparation :

- Perform data cleansing, preprocessing, and feature engineering for large and complex datasets.

- Work with SQL and other data extraction tools to retrieve and manipulate data from relational databases.

Model Deployment & MLOps :

- Deploy ML/DL models into production using REST APIs built with Flask or FastAPI.

- Utilize cloud platforms (AWS, Azure, GCP) to deploy and manage AI workloads.

- Implement MLOps best practices using tools like MLflow, Airflow, Docker, and version control systems.

- Build automated pipelines for data processing, model training, and model monitoring.

Performance Tuning & Optimization :

- Conduct hyperparameter tuning, performance benchmarking, and error analysis.

- Optimize model performance for speed, accuracy, scalability, and resource efficiency.

Cross-functional Collaboration :

- Work closely with product, engineering, and business teams to understand requirements and convert them into AI-driven solutions.

- Document workflows, model details, deployment processes, and best practices.

Research & Innovation :

- Stay current with advancements in AI/ML, including LLMs, generative AI, computer vision, and MLOps trends.

- Experiment with new techniques to improve model accuracy, robustness, and scalability.

Required Skills & Qualifications :

Programming & Tools :

- Strong proficiency in Python and relevant libraries : NumPy, Pandas, Scikit-learn, TensorFlow or PyTorch.

- Experience building APIs using Flask or FastAPI.

- Hands-on experience with containerization (Docker).

Machine Learning & Deep Learning :

- Solid understanding of ML algorithms, model training, evaluation, and optimization.

- Practical experience with deep learning architectures including CNNs and Transformers.

Data & Cloud Technologies :

- Strong SQL skills and experience working with large datasets.

- Expertise in at least one cloud platform-AWS, Azure, or GCP.

- Understanding of data pipeline design and cloud-based deployments.

MLOps :

- Experience with tools such as MLflow, Airflow, or similar pipeline/orchestration platforms.

Mathematics :

- Good grasp of statistics, linear algebra, probability, and ML mathematical foundations.

Preferred Skills :

- Hands-on experience with Large Language Models (LLMs) and Natural Language Processing (NLP).

- Exposure to Computer Vision projects.

- Knowledge of vector databases, embeddings, and RAG pipelines.

What We Offer :

- Opportunity to work on cutting-edge AI initiatives and large-scale enterprise projects.

- Innovative, collaborative, and remote-first work culture.

- Competitive compensation and benefits package.

- Professional growth through continuous learning, experimentation, and mentorship