Image Processing Engineer

Job Overview:

As a Technical Lead, you will be responsible for leading the design, development, and deployment of AI-powered Edtech solutions. You will mentor a team of engineers, collaborate with data scientists, and work closely with product managers to build scalable and efficient AI systems. The ideal candidate should have 8-10 years of experience in software development, machine learning, AI use case development and product creation along  with strong expertise in cloud-based architectures.

Key Responsibilities:

AI Tutor & Simulation Intelligence

• Architect the AI intelligence layer that drives contextual tutoring, retrieval-based reasoning, and fact-grounded explanations.
• Build RAG (retrieval-augmented generation) pipelines and integrate verified academic datasets from textbooks and internal course notes.
• Connect the AI Tutor with the Simulation Lab, enabling dynamic feedback — the system should read experiment results, interpret them, and explain why outcomes occur.
• Ensure AI responses remain transparent, syllabus-aligned, and pedagogically accurate.

Platform & System Architecture

• Lead the development of a modular, full-stack platform unifying courses, explainers, AI chat, and simulation windows in a single environment.
• Design microservice architectures with API bridges across content systems, AI inference, user data, and analytics.
• Drive performance, scalability, and platform stability — every millisecond and every click should feel seamless.

Reliability, Security & Analytics

• Establish system observability and monitoring pipelines (usage, engagement, AI accuracy).
• Build frameworks for ethical AI, ensuring transparency, privacy, and student safety.
• Set up real-time learning analytics to measure comprehension and identify concept gaps.

Leadership & Collaboration

• Mentor and elevate engineers across backend, ML, and front-end teams.
• Collaborate with the academic and product teams to translate physics pedagogy into engineering precision.
• Evaluate and integrate emerging tools — multi-modal AI, agent frameworks, explainable AI — into the product roadmap.

Qualifications & Skills:

• 8–10 years of experience in software engineering, ML systems, or scalable AI product builds.
• Proven success leading cross-functional AI/ML and full-stack teams through 0→1 and scale-up phases.
• Expertise in cloud architecture (AWS/GCP/Azure) and containerization (Docker, Kubernetes).
• Experience designing microservices and API ecosystems for high-concurrency platforms.
• Strong knowledge of LLM fine-tuning, RAG pipelines, and vector databases (Pinecone, Weaviate, etc.).
• Demonstrated ability to work with educational data, content pipelines, and real-time systems.

Bonus Skills (Nice to Have):

• Experience with multi-modal AI models (text, image, audio, video).
• Knowledge of AI safety, ethical AI, and explain ability techniques.
• Prior work in AI-powered automation tools or AI-driven SaaS products.

About Us

Mobileum is a leading provider of Telecom analytics solutions for roaming, core network, security, risk management, domestic and international connectivity testing, and customer intelligence.

More than 1,000 customers rely on its Active Intelligence platform, which provides advanced analytics solutions, allowing customers to connect deep network and operational intelligence with real-time actions that increase revenue, improve customer experience, and reduce costs.

Headquartered in Silicon Valley, Mobileum has global offices in Australia, Dubai, Germany, Greece, India, Portugal, Singapore and UK with global HC of over 1800+. 

Join Mobileum Team

At Mobileum we recognize that our team is the main reason for our success. What does work with us mean? Opportunities!

Role: GenAI/LLM Engineer – Domain-Specific AI Solutions (Telecom)

About the Job

We are seeking a highly skilled GenAI/LLM Engineer to design, fine-tune, and operationalize Large Language Models (LLMs) for telecom business applications. This role will be instrumental in building domain-specific GenAI solutions, including the development of domain-specific LLMs, to transform telecom operational processes, customer interactions, and internal decision-making workflows.

Roles & Responsibility:

• Build domain-specific LLMs by curating domain-relevant datasets and training/fine-tuning LLMs tailored for telecom use cases.
• Fine-tune pre-trained LLMs (e.g., GPT, Llama, Mistral) using telecom-specific datasets to improve task accuracy and relevance.
• Design and implement prompt engineering frameworks, optimize prompt construction and context strategies for telco-specific queries and processes.
• Develop Retrieval-Augmented Generation (RAG) pipelines integrated with vector databases (e.g., FAISS, Pinecone) to enhance LLM performance on internal knowledge.
• Build multi-agent LLM pipelines using orchestration tools (LangChain, LlamaIndex) to support complex telecom workflows.
• Collaborate cross-functionally with data engineers, product teams, and domain experts to translate telecom business logic into GenAI workflows.
• Conduct systematic model evaluation focused on minimizing hallucinations, improving domain-specific accuracy, and tracking performance improvements on business KPIs.
• Contribute to the development of internal reusable GenAI modules, coding standards, and best practices documentation.

Desired Profile

• Familiarity with multi-modal LLMs (text + tabular/time-series).
• Experience with OpenAI function calling, LangGraph, or agent-based orchestration.
• Exposure to telecom datasets (e.g., call records, customer tickets, network logs).
• Experience with low-latency inference optimization (e.g., quantization, distillation).

Technical skills

• Hands-on experience in fine-tuning transformer models, prompt engineering, and RAG architecture design.
• Experience delivering production-ready AI solutions in enterprise environments; telecom exposure is a plus.
• Advanced knowledge of transformer architectures, fine-tuning techniques (LoRA, PEFT, adapters), and transfer learning.
• Proficiency in Python, with significant experience using PyTorch, Hugging Face Transformers, and related NLP libraries.
• Practical expertise in prompt engineering, RAG pipelines, and LLM orchestration tools (LangChain, LlamaIndex).
• Ability to build domain-adapted LLMs, from data preparation to final model deployment.

Work Experience

7+ years of professional experience in AI/ML, with at least 2+ years of practical exposure to LLMs or GenAI deployments.

Educational Qualification

• Master’s or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Natural Language Processing, or a related field.
• Ph.D. preferred for foundational model work and advanced research focus.

Responsibilities:

• Collaborating with data scientists and machine learning engineers to understand their requirements and design scalable, reliable, and efficient machine learning platform solutions.
• Building and maintaining the applications and infrastructure to support end-to-end machine learning workflows, including inference and continual training.
• Developing systems for the definition deployment and operation of the different phases of the machine learning and data life cycles.
• Working within Kubernetes to orchestrate and manage containers, ensuring high availability and fault tolerance of applications.
• Documenting the platform's best practices, guidelines, and standard operating procedures and contributing to knowledge sharing within the team.

Requirements:

• 3+ years of hands-on experience in developing and managing machine learning or data platforms
• Proficiency in programming languages commonly used in machine learning and data applications such as Python, Rust, Bash, Go
• Experience with containerization technologies, such as Docker, and container orchestration platforms like Kubernetes.
• Familiarity with CI/CD pipelines for automated model training and deployment. Basic understanding of DevOps principles and practices.
• Knowledge of data storage solutions and database technologies commonly used in machine learning and data workflows.

Job Description
Lead Machine Learning (ML)/
NLP Engineer
5 + years of experience

About Contify
Contify is an AI-enabled Market and Competitive Intelligence (MCI)
software to help professionals make informed decisions. Its B2B SaaS
platform helps leading organizations such as Ericsson, EY, Wipro,
Deloitte, L&T, BCG, MetLife, etc. track information on their competitors,
customers, industries, and topics of interest by continuously monitoring
over 500,000+ sources on a real-time basis. Contify is rapidly growing
with 185+ people across two offices in India. Contify is the winner of
Frost and Sullivan’s Product Innovation Award for Market and
Competitive Intelligence Platforms.

The role
We are looking for a hardworking, aspirational, and innovative
engineering person for the Lead ML/ NLP Engineer position. You’ll build
Contify’s ML and NLP capabilities and help us extract value from
unstructured data. Using advanced NLP, ML, and text analytics, you will
develop applications that will extract business insights by analyzing a
large amount of unstructured text information, identifying patterns, and
by connecting the events.
Responsibilities:
You will be responsible for all the processes from data collection, and
pre-processing, to training models and deploying them to production.
➔ Understand the business objectives; design and deploy scalable
ML models/ NLP applications to meet those objectives
➔ Use of NLP techniques for text representation, semantic analysis,
information extraction, to meet the business objectives in an
efficient manner along with metrics to measure progress
➔ Extend existing ML libraries and frameworks and use effective text
representations to transform natural language into useful features
➔ Defining and supervising the data collection process, verifying data
quality, and employing data augmentation techniques
➔ Defining the preprocessing or feature engineering to be done on a
given dataset
➔ Analyze the errors of the model and design strategies to overcome
them
➔ Research and implement the right algorithms and tools for ML/
NLP tasks
➔ Collaborate with engineering and product development teams
➔ Represent Contify in external ML industry events and publish
thought leadership articles

Desired Skills and Experience
To succeed in this role, you should possess outstanding skills in
statistical analysis, machine learning methods, and text representation
techniques.
➔ Deep understanding of text representation techniques (such as n-
grams, bag of words, sentiment analysis, etc), statistics and
classification algorithms
➔ Hand on experience in feature extraction techniques for text
classification and topic mining
➔ Knowledge of text analytics with a strong understanding of NLP
algorithms and models (GLMs, SVM, PCA, NB, Clustering, DTs)
and their underlying computational and probabilistic statistics
◆ Word Embedding like Tfidf, Word2Vec, GLove, FastText, etc.
◆ Language models like Bert, GPT,  RoBERTa, XLNet 
◆ Neural networks like RNN, GRU, LSTM, Bi-LSTM
◆ Classification algorithms like LinearSVC, SVM, LR
◆ XGB, MultinomialNB, etc.
◆ Other Algos- PCA, Clustering methods, etc
➔ Excellent knowledge and demonstrable experience in using NLP
packages such as NLTK, Word2Vec, SpaCy, Gensim, Standford
CoreNLP, TensorFlow/ PyTorch.
➔ Experience in setting up supervised & unsupervised learning
models including data cleaning, data analytics, feature creation,
model selection & ensemble methods, performance metrics &
visualization
➔ Evaluation Metrics- Root Mean Squared Error, Confusion Matrix, F
Score, AUC – ROC, etc
➔ Understanding of knowledge graph will be a plus


Qualifications
➔ Education: Bachelors or Masters in Computer Science,
Mathematics, Computational Linguistics or similar field
➔ At least 4 years' experience building Machine Learning & NLP
solutions over open-source platforms such as SciKit-Learn,
Tensorflow, SparkML, etc
➔ At least 2 years' experience in designing and developing
enterprise-scale NLP solutions in one or more of: Named Entity
Recognition, Document Classification, Feature Extraction, Triplet
Extraction, Clustering, Summarization, Topic Modelling, Dialog
Systems, Sentiment Analysis
➔ Self-starter who can see the big picture, and prioritize your work to
make the largest impact on the business’ and customer’s vision
and requirements
➔ Being a committer or a contributor to an open-source project is a
plus

Note
Contify is a people-oriented company. Emotional intelligence, therefore,
is a must. You should enjoy working in a team environment, supporting
your teammates in pursuit of our common goals, and working with your
colleagues to drive customer value. You strive to not only improve
yourself, but also those around you.

What you’ll do:

• Will have a unique and rewarding opportunity to shape and design an app with a huge impact on the Automotive industry
• Write highly scalable software in Swift ad Kotlin with a focus on reusability and efficiency
• Work with some of the best people in the industry to build and maintain compelling user experiences
• Working with iOS Frameworks such as AVFoundation/video streaming, CoreML
• Work with open-source multimedia projects, such as FFmpeg

What you’ll bring:

• 5+ years of iOS/Android development.
• Strong background in software engineering with large-scale apps
• Experience with iOS/Android SDKs
• Expert knowledge of XCode/AppCode IDE, build and distribution processes
• Experience writing multi-threaded/asynchronous code
• Creative and innovative problem-solving skills with a passion for new technologies
• Strong team player and ability to work without many directions when needed

Bonus points for:

• B.Sc./M.Sc. in Computer Science or related fields
• Knowledge of C/C++
• Background/experience in AI (e.g. deep learning, computer vision)
• Contributions to community software

Note: We are looking for immediate joiners. Selected/Offered candidates can ready to join within 15 to 30 days of time can apply.