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Infospica Consultancy Services

2707 - Yamuna, Phase III SEZ Campus, Technopark, Thiruvananthapuram, Kerala, India , 695583

Junior AI Engineer

Closing Date:10,July 2026
Job Published: 09,June 2026
Contact Email: jobs@infospica.com

Brief Description

We are building an early-stage AI team and looking for a Junior AI Engineer to help design and ship AI/ML solutions for business workflows. You will work in a team, combining hands-on coding, model development, and experimentation with local LLMs (via Ollama) to automate and optimize operations.

 

Mandatory Skills:

• AI/ML models, Python, Core ML concepts, ML framework (Scikit‑learn/TensorFlow/PyTorch), MLOps, SQL/NoSQL, Messaging/queue systems

Key Responsibilities:

• Build and maintain AI/ML solutions focused on business workflows. 

• Implement end‑to‑end pipelines: data collection, preprocessing, feature engineering, model training, evaluation, and deployment. 

• Work with local LLMs (via Ollama) and traditional ML models to solve practical automation problems. 

• Set up initial MLOps practices from scratch (basic experiment tracking, versioning, simple CI/CD and monitoring for models). 

• Collaborate with senior engineers on solution design while spending most of your time writing and improving code. 

• Integrate models into applications and services through APIs or microservices. 

• Prepare clear documentation of data flows, model behavior, assumptions, and limitations. 

• Participate in client demos and discussions to showcase AI solutions and understand requirements. 

• Contribute to AI governance activities such as documenting risks, bias considerations, and approval workflows for new AI features. 

Preferred Skills

Required Qualifications:

• 0–1 year of experience as an AI/ML Engineer, Data Scientist, or similar role, or strong academic/personal projects in AI/ML. 

• Bachelor’s degree in Computer Science, Engineering, Data Science, Mathematics, or equivalent practical experience. 

• Solid Python skills for data processing and model development. 

• Understanding of core ML concepts: supervised/unsupervised learning, evaluation metrics, overfitting, etc. 

• Experience with at least one ML framework (e.g., scikit‑learn, TensorFlow, or PyTorch). 

• Ability to work with databases (SQL/NoSQL) and basic messaging/queue systems to move data in and out of models. 

• Strong problem‑solving mindset, eagerness to learn, and comfort working in a fast‑moving environment. 

• Good communication skills and willingness to collaborate in a team and with non‑technical stakeholders. 

Nice to Have:

• Experience running or fine‑tuning local LLMs (e.g., via Ollama) or other open‑source models. 

• Exposure to workflow automation, or operations-heavy domains. 

• Familiarity with basic MLOps tools (MLflow, DVC, Weights & Biases) and containerization (Docker). 

• Basic knowledge of any cloud platform (AWS, Azure, GCP) for deploying services. 

• Experience integrating ML models into web backends (REST APIs, microservices, Node.js/Next.js). 

• Understanding of vector databases or simple retrieval/RAG systems for LLM-based solutions. 

• Awareness of ethical AI, bias, and privacy considerations.