AI/ML Engineer

##  Job Opening: AI/ML Engineer

Location: Full Remote
Job Type: Full-Time  
Salary Range: $3,000 – $6,000 USD / month
Experience Level: Mid to Senior (3–5+ years)

---

###  About the Role

We're seeking a versatile and innovative AI/ML Engineer to join our growing team. This role sits at the intersection of data science, machine learning, NLP, and software engineering. You'll be designing and deploying production-grade machine learning systems, experimenting with cutting-edge LLMs, and solving real-world problems using unsupervised learning, graph-based models, and distributed systems.

You’ll collaborate cross-functionally with product managers, designers, and engineers to shape how we leverage AI across our platforms—from education to healthcare.

---

###  Responsibilities

- Design, prototype, train, and deploy LLMs and traditional ML models for:
 - Semantic understanding, emotion detection, expressive summarization  
 - Text clustering, topic modeling, and classification  
 - Intent/sentiment extraction and entity resolution  
 - Recommendation systems and agentic RAG systems  
- Develop clean, scalable ML pipelines and integrate them with existing systems using APIs and batch services  
- Collaborate with cross-functional teams to understand user needs and translate them into AI-powered solutions  
- Manage full ML lifecycle: from data wrangling (SQL, pipelines) to model deployment (cloud-based environments)  
- Build knowledge graphs and explore Graph Neural Networks (GNNs) for structured reasoning  
- Experiment with new ML approaches and keep up with advances in modern NLP and distributed inference  
- Monitor, evaluate, and continuously improve model performance in production  
- Document solutions and communicate results clearly to both technical and non-technical stakeholders  

---

###  Requirements

- 3–7+ years of experience building and deploying ML systems (production experience a must)  
- Strong hands-on skills in:
 - Python and SQL  
 - NLP libraries (Spacy, NLTK, HuggingFace, etc.)  
 - Deep learning frameworks (PyTorch, TensorFlow, JAX)  
- Working knowledge of:
 - Modern NLP and LLM finetuning  
 - Unsupervised techniques like clustering and topic modeling  
 - Semantic similarity, summarization, classification, sentiment/emotion detection  
 - Distributed training/inference and cloud infrastructure (AWS, Azure, or GCP)  
- Experience with:
 - Microservices and API integrations  
 - Docker, Kubernetes, and containerized ML deployments  
 - MLOps practices: CI/CD for ML, model monitoring, and pipeline automation  
- Familiarity with domain-driven design and scalable, decoupled architectures  
- Strong communication and storytelling ability to tie technical work to product and business outcomes  

---

###  Bonus Skills

- Experience with graph-based ML (Knowledge Graphs, GNNs, DGL)  
- Exposure to networked, multi-rank GPU environments  
- Background in data engineering or DevOps  
- Data visualization for ML explainability and diagnostics  
- Passion for education, healthcare, or social impact applications  

---

###  Who You Are

- You connect the dots: You see the big picture and align your work with user and business impact.  
- You make high-leverage bets: You act strategically with speed and resourcefulness.  
- You simplify and ship: You focus on essentials, iterate fast, and get things into production.  
- You think from first principles: You question assumptions and explore new paths.  
- You’re naturally curious and proactive about learning and experimenting.

---

###  What We Offer

- Competitive compensation and performance-based bonuses  
- Flexible hybrid/remote work schedule  
- Health, dental, and vision insurance  
- A collaborative, mission-driven team environment  
- Opportunities for professional growth, mentorship, and innovation  
- The chance to work with cutting-edge ML systems in a meaningful space