Abrar Admin

Skylabs AI

<div>About Us
At SkyLabs AI Inc., we are at the forefront of the artificial intelligence revolution. As a US-headquartered company, we conduct applied research on AI for intelligent reasoning. We specialize in complex neurosymbolic AI to solve intricate problems within software engineering. Our team is composed of world-class researchers and engineers dedicated to building the platforms and intelligent agents that will power the next generation of software. If you are passionate about building truly intelligent systems and want to make a lasting impact, join us.
About the Role 
We are seeking an exceptional Technical Lead to define and execute the technical vision for a pioneering project at the confluence of pure mathematics, artificial intelligence, and formal verification. This role is a unique hybrid, blending state-of-the-art software engineering with cutting-edge academic research. You will not only architect and lead the development of our AI-powered platform for formalizing and proving mathematics in LEAN 4 and Rocq, but you will also act as a key bridge to the academic world. The ideal candidate is a hands-on expert passionate about building robust systems for machine-checked proofs and eager to collaborate with the global research community to advance the field.
Requirements
Key Responsibilities<ul>
<li>
Technical Vision &amp; Architecture: Define and drive the technical strategy for formalizing mathematics at scale. Design robust, scalable software architecture for our data pipeline, AI models, and proof libraries.</li>
<li>Hands-On Development &amp; Prototyping: Lead by example with hands-on contributions to the core codebase. Develop proofs-of-concept and tackle the most challenging technical problems in proof formalization and AI model implementation.</li>
<li>Academic Collaboration &amp; Research: Establish and maintain active collaborations with leading researchers, university labs, and academic institutions. Co-author research papers for top-tier conferences and journals, and represent our work within the scientific community.</li>
<li>AI Strategy &amp; Implementation: Direct the research, experimentation, and application of advanced AI models (e.g., Large Language Models) for the task of autoformalization&mdash;translating informal math into formal LEAN 4 code and/or Rocq.</li>
<li>Team Mentorship &amp; Guidance: Mentor a talented team of mathematicians and software engineers. Foster a culture of technical excellence, intellectual curiosity, and rigorous engineering practices.</li>
<li>Code &amp; Proof Quality: Set and enforce the highest standards for mathematical correctness, code quality, and the verifiability of formalized proofs. Champion best practices in software development, version control (Git), and formal methods.</li>
</ul>
Required Qualifications<ul>
<li>
Education: A PhD in Mathematics or Computer Science is strongly preferred. A Master's degree with an outstanding track record of relevant research and development will be considered.</li>
<li>Mathematical Depth: A sophisticated understanding of graduate-level mathematics across several domains</li>
<li>AI &amp; NLP Proficiency: Proven experience applying AI/ML, particularly large language models (LLMs)</li>
<li>Software Engineering Excellence: Strong software development skills, with proficiency in languages like Python and a deep understanding of system design and architecture.</li>
<li>Research Acumen: Demonstrable ability to engage with and contribute to academic research, evidenced by publications, conference presentations, or significant contributions to academic research projects.</li>
</ul>
Preferred Qualifications<ul>
<li>
Expertise in Formal Methods: Deep, hands-on expertise with proof assistants. Significant experience with LEAN 4 and/or Rocq is highly desired. A portfolio of non-trivial formalization projects is a major plus.</li>
<li>A strong publication record in relevant fields (e.g., formal methods, automated reasoning, AI, computational mathematics).</li>
<li>Experience leading or making significant contributions to major open-source formal methods or AI projects.</li>
<li>Experience presenting at top-tier academic conferences.</li>
</ul>
Benefits<ul>
<li>
Salaries in USD (income tax exemptions)</li>
<li>Work in Pakistan Timezone</li>
<li>Comprehensive health allowance</li>
<li>Monthly team events and activities</li>
<li>Relocation allowance (if you're moving to Islamabad)</li>
<li>Opportunity to work with top minds in the industry and academia</li>
<li>Startup culture where ideas are heard at all levels</li>
<li>Adequate annual, sick, casual and parental leaves</li></ul></div>

Technical Lead - AI for Math

<div>About Us
At SkyLabs AI Inc., we are at the forefront of the artificial intelligence revolution. As a US-headquartered company, we conduct applied research on AI for intelligent reasoning. We specialize in complex neurosymbolic AI to solve intricate problems within software engineering. Our team is composed of world-class researchers and engineers dedicated to building the platforms and intelligent agents that will power the next generation of software. If you are passionate about building truly intelligent systems and want to make a lasting impact, join us.
The Role
We are seeking an exceptional Senior AI Research Engineer with a strong focus on training and improving LLMs across the full lifecycle&mdash;from Domain‑Adaptive Pretraining to Supervised Fine‑Tuning (SFT), RL/RLVR, and advanced post‑training techniques (e.g., reward modeling, preference optimization, RL‑VR style workflows). You will lead hands‑on training efforts, contribute to research direction, and build robust pipelines for data, training, evaluation, and deployment.
You should have in‑depth understanding of LLM internals (attention/MLP dynamics, normalization, optimization behavior, scaling laws), and modern architectures including Mixture of Experts (MoE) and other frontier design choices. You will work closely with product and platform teams to translate research ideas into performant systems.
Requirements
Key Responsibilities<ul>
<li>
Lead the team of AI Engineers/Researchers
</li><li>Train and iterate on LLMs end-to-end across DAPT/CPT, SFT, and RL-based post-training (preference optimization, reward modeling, verifiable rewards, policy optimization, and related variants).
</li><li>Design training recipes: tokenization strategy, curriculum/sampling, batch/sequence packing, optimizer + scheduler choices, stability techniques, and hyperparameter search.
</li><li>Architect and implement efficient training systems using distributed training (data/tensor/pipeline parallelism), FSDP/ZeRO, activation checkpointing, mixed precision, and throughput optimization.
</li><li>Develop and maintain LLM data pipelines: large-scale data ingestion, filtering, deduplication, contamination checks, domain balancing, safety filtering, and dataset versioning.
</li><li>Perform deep EDA and root-cause analysis for training/eval regressions (loss spikes, instability, alignment drift, memorization, toxicity, domain overfitting), and implement mitigations.
</li><li>Build evaluation and benchmarking suites: offline metrics, human preference pipelines, automatic evals, domain-specific test sets, adversarial probing, and model behavior tracking over time.
</li><li>Apply and advance model compression and efficiency: distillation from LLMs, quantization-aware considerations, pruning/sparsity (including MoE routing behavior), and inference-time optimization tradeoffs.
</li><li>Implement and operationalize LLMOps: experiment tracking, reproducible runs, model registry, training telemetry, artifact management, CI for training configs, and safe rollout strategies.
</li><li>Leverage AI coding tools (e.g., Cursor, Copilot) to accelerate development while maintaining strong engineering rigor, testability, and code review standards.
</li><li>Collaborate cross-functionally with platform, infra, and product teams to integrate trained models into agentic/production pipelines (retrieval, tool use, evaluation gates, monitoring).
</li><li>Stay current with the field and translate new ideas (architectures, post-training, data strategies, evals) into internal experiments and improvements.
</li></ul>Qualifications &amp; Skills<ul>
<li>
5+ years in ML engineering / applied research, with significant hands-on experience training large models, especially LLMs.
</li><li>Strong practical knowledge of transformer internals and modern variations (MoE, routing, load balancing, attention variants, normalization choices, long-context strategies).
</li><li>Demonstrated experience with DAPT/CPT, SFT, and RL-based post-training (e.g., reward modeling, preference datasets, verifiable rewards, policy optimization). Ability to reason about why a method works and when it fails.
</li><li>Excellent understanding of data science fundamentals: EDA, dataset design, bias/contamination, sampling strategies, and error analysis.
</li><li>Proven ability to root-cause and debug training instabilities and performance regressions (numerics, data issues, infra bottlenecks, config drift).
</li><li>Expert-level programming in Python, with strong software engineering fundamentals (data structures, algorithms, systems thinking).
</li><li>Experience with key tooling such as PyTorch, distributed training frameworks (FSDP/DeepSpeed/ZeRO), and training orchestration.
</li><li>Familiarity with LLMOps: tracking (e.g., W&amp;B/MLflow), dataset versioning, reproducibility, deployment constraints, and monitoring of model behavior.
</li><li>Comfortable building agentic pipelines around LLMs (evaluation agents, data generation/labeling loops, model-in-the-loop distillation, automated red-teaming).
</li><li>Bonus: publications, open-source contributions, or demonstrated leadership in shipping LLM training improvements.
</li></ul>Who You Are
You&rsquo;re a pragmatic researcher-engineer: you can read papers, run experiments, and also build the training and data systems that make results reproducible and shippable. You&rsquo;re meticulous about data and measurement, fast at debugging, and comfortable making tradeoffs between quality, cost, and timeline. You communicate clearly, mentor others, and thrive in an environment where you&rsquo;re trusted to drive big initiatives.
Benefits<ul>
<li>
Salaries in USD (income tax exemptions)</li>
<li>Work in Pakistan Timezone</li>
<li>Comprehensive health allowance</li>
<li>Monthly team events and activities</li>
<li>Relocation allowance (if you're moving to Islamabad)</li>
<li>Opportunity to work with top minds in the industry and academia</li>
<li>Startup culture where ideas are heard at all levels</li>
<li>Adequate annual, sick, casual and parental leaves</li></ul></div>

Senior AI Research Engineer

<div>About Us
At SkyLabs AI Inc., we are at the forefront of the artificial intelligence revolution. As a US-headquartered company, we conduct applied research on AI for intelligent reasoning. We specialize in complex neurosymbolic AI to solve intricate problems within software engineering. Our team is composed of world-class researchers and engineers dedicated to building the platforms and intelligent agents that will power the next generation of software. If you are passionate about building truly intelligent systems and want to make a lasting impact, join us.
Key Responsibilities<ul><li>
Tech Recruiting: Work closely with hiring managers to hire top talent for various teams - 80% of the work</li><li>
People Operation: Manage the employee lifecycle from on-boarding to off-boarding</li><li>
HR Functions: Develop and implement HR policies and procedures</li><li>
Operations: Handle correspondence with admin, partners, collaborators, oversee office logistics</li><li>
Performance reviews: Assisting manager with performance reviews</li></ul> 

Requirements 
<ul><li>
Have very good experience in sourcing top tech talent.</li><li>
Someone who is not afraid to wear many hats and taking multiple responsibilities</li><li>
Have experience working at startups or fast growing companies in people/HR department</li><li>
At-least 4 year of experience to be successful in this role</li><li>
Have excellent communication and interpersonal skills</li><li>
Ability to work independently and in a team</li><li>
Good with tools such as ATS such as Workable, Linkedin, google sheets and docs, data analysis</li><li>
Good with utilizing AI tools such as Gemini and ChatGPT to enhance productivity and skill</li></ul> 

Benefits 
<ul><li>
Salaries in USD (income tax exemptions)</li><li>
Work in Pakistan Timezone</li><li>
Comprehensive health allowance</li><li>
Monthly team events and activities</li><li>
Relocation allowance (if you're moving to Islamabad)</li><li>
Opportunity to work with top minds in the industry and academia</li><li>
Startup culture where ideas are heard at all levels</li><li>
Adequate annual, sick, casual and parental leaves</li></ul></div>

Human Resources Lead

<div>About Us
At SkyLabs AI Inc., we are at the forefront of the artificial intelligence revolution. As a US-headquartered company, we conduct applied research on AI for intelligent reasoning. We specialize in complex neurosymbolic AI to solve intricate problems within software engineering. Our team is composed of world-class researchers and engineers dedicated to building the platforms and intelligent agents that will power the next generation of software. If you are passionate about building truly intelligent systems and want to make a lasting impact, join us.
About the Summer Internship
Join us for a hands-on AI engineering internship where you&rsquo;ll work across the modern LLM stack. You&rsquo;ll help design and build AI Agents, learn and apply Formal Verification of Software, and contribute to data pipelines. You&rsquo;ll also support data curation, dataset creation and distillation, and participate in training and improving large language models&mdash;including continuous pre-training, supervised fine-tuning (SFT), and reinforcement learning (RL) workflows. As part of the role, you&rsquo;ll get up to speed on software verification using formal methods in Rocq and strengthen quality practices through property-based testing techniques. This role is ideal if you enjoy building real systems, learning fast, and working at the intersection of research and engineering. 
 
Duration: 3 months (June 2026 through August 2026) On-site - Full-time
Requirements
Desirable Candidates<ul>
<li>
High aptitude and strong problem-solving skills
</li><li>Have studied courses in programming, AI (including Generative AI), and mathematics
</li><li>Comfortable coding in Python (data handling, scripting, and building prototypes)
</li><li>Good with using AI Coding IDEs/CLIs</li>
</ul>
Preference<ul><li>
You are in your final year or have already graduated
</li></ul>
Benefits<ul>
<li>
$100 stipend per month</li>
<li>Opportunity to work on state of the art technologies</li>
<li>Opportunity to work with top minds in the industry</li></ul></div>

AI Engineering Intern (Gen AI, Agents & Formal Verification) - Paid

Join Skylabs AI and explore 4   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

Skylabs AI

About Company

Technical Lead - AI for Math

Senior AI Research Engineer

Human Resources Lead

AI Engineering Intern (Gen AI, Agents & Formal Verification) - Paid