
Ai/ML Engineer
17 hours ago
Mid‑Level AI/ML Engineer (Experienced Professionals Only)
Company:
Mobitising Inc.
Location:
Karachi (Onsite)
Experience:
Minimum
2+ years
in AI/ML engineering
Employment Type:
Full-Time
Role Overview
Join Mobitising's AI team to work on thrilling projects across
generative models
,
agentic systems
,
multi‑modal AI
, and robust predictive systems. You'll be involved in everything from
data acquisition and cleaning
to
LLM fine‑tuning
and
production deployments
, ensuring real-world innovation and product impact.
Key Responsibilities
l Design and deploy models in areas such as:
TTS (Text‑to‑Speech)
and
Speech Recognition
OCR
,
Image/Video/Music Generation
,
Vision
(CNNs, GANs, Detectron2)
Prompt Engineering
,
RAG pipelines
,
Agentic AI systems
,
LLMOps
,
LLM fine‑tuning
l Implement NLP-based projects including summarization, chatbots, sentiment analysis using Hugging Face, spaCy, NLTK
l Scrape, integrate, and preprocess large-scale datasets using
API integration
,
web crawling
,
ETL automation
,
Spark
,
Kafka
,
dbt
,
Airflow
l Build MLOps pipelines for reproducible ML production:
CI/CD
,
versioning
,
monitoring
,
model compression
,
pruning
,
quantization
l Optimize deployments including
edge AI/inference
, using frameworks like TensorFlow Lite, PyTorch Mobile, NVIDIA Jetson, AWS IoT Greengrass, Azure IoT Edge
Technical Stack
l
Programming:
Python (NumPy, Pandas, scikit‑learn), JavaScript; familiarity with Rust or JAX a plus
l
Frameworks/Libraries:
Django, PyTorch 2.0, TensorFlow, Keras, OpenCV, Stable Baselines or Gym (for RL), Hugging Face Transformers
l
Large Language Models & Tools:
LLM fine‑tuning, prompt chaining and engineering, LangChain, RAG systems, vLLMs, gemini/OpenAI / Anthropic / Hugging Face APIs
l
AI Agents & Autonomous Systems:
Agentic AI development using reinforcement learning, multi-agent orchestration
l
Databases & Backend:
frontend, FastAPI/Django backend, relational/non-relational databases, vector DBs (FAISS, Weaviate)
l
Cloud & DevOps:
AWS (SageMaker, Bedrock), GCP (Vertex AI), Azure ML; containerization with Docker/Kubernetes; MLOps tools like MLflow, Kubeflow, TFX
Additional Responsibilities
l Collaborate in an Agile environment using Git workflows, Jira, and CI/CD pipelines
l Ensure
responsible AI
: implement fairness, bias mitigation, explainability (XAI), privacy-preserving methods (differential privacy, homomorphic encryption) and follow legal frameworks (e.g., EU AI Act, GDPR)
l Keep pace with
AI ethics, governance
, and regulatory trends
l Translate AI models into tangible business outcomes and user value
Required Skills
l Solid foundation in
Python
,
Django
, and
l Demonstrated experience with
machine learning
,
deep learning
, and
LLMs
l Hands-on in
data scraping
,
ETL pipelines
, and data preprocessing
l Proficiency with
prompt engineering
,
LLM fine-tuning
,
RAG
,
agentic systems
l Full-stack delivery: backend API development and frontend integration
l Experience in
containerized deployment
,
MLOps automation
, and
monitoring
l Strong algorithmic thinking: OOP, data structures, DSA, algorithm analysis
Preferred Qualifications
l Bachelor's or Master's in CS, AI, Data Science, or related field
l 2+ years of industry experience working with modern AI engineering challenges
l Portfolio featuring GitHub, open-source contributions, or demonstrated AI production results
l Experience with
edge AI
,
reinforcement learning
,
graph neural networks
or
Rust/JAX optimization
To Apply:
Send your resume to
Subject:
Application for
Mid‑Level AI/ML Engineer
Become a part of our growing tech family at MobiTising — where innovation meets opportunity
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