Join Mecka AI as a Research Scientist to advance multimodal foundation models and tackle challenging research problems.
Posted by employer 1 day ago
First seen on Joblaze 16 hours ago
Last verified on the company career page 16 hours ago
Skills & Technologies
What you'll build
- Research, develop, and improve vision-language models
- Design and implement advanced training strategies
- Investigate approaches to improve reasoning and training efficiency
- Develop strategies for data curation and synthetic data generation
- Design experiments and evaluation frameworks
Must have
- Hands-on experience researching, training, fine-tuning large-scale foundation models
- Strong understanding of deep learning architectures
- Practical experience with supervised fine-tuning or reinforcement learning
- Strong proficiency in Python and PyTorch, JAX
- Experience designing and analyzing large-scale machine learning experiments
- Research publications on top-tier journals/conferences
Nice to have
- Experience with large-scale model post-training and reinforcement learning
- Familiarity with multimodal data pipelines
- Experience with reward modeling or synthetic data generation
- Experience improving model capabilities through innovations in training strategies
AI in the day-to-day
Mecka uses AI responsibly to support administrative and efficiency-focused aspects of our recruitment process.
Not disclosed in this posting: compensation, years of experience, work arrangement, visa sponsorship.
Joblaze summary
In this role, the Research Scientist focuses on enhancing large-scale vision-language and multimodal foundation models through hands-on experimentation and innovative training strategies. Key skills include deep learning expertise, proficiency in Python and frameworks like PyTorch or JAX, and experience with model optimization and evaluation. This position is ideal for someone with a strong research background and a track record in AI, particularly in multimodal systems. Mecka AI emphasizes collaboration with robotics teams, aiming to bridge the gap between theoretical research and practical applications.
Joblaze insights
Quick facts
- What's the tech stack?
- Joblaze extracted these technologies from the posting: JAX, Multimodal Models, PyTorch, Python, reinforcement learning, vision-language models.
- What seniority level is this role?
- Mecka AI targets senior candidates for this position.
- Is this full-time or contract?
- Full-time for this Research Scientist – Multimodal Foundation Models role at Mecka AI.
From the original posting
The Role
We're looking for an experienced Research Scientist to advance the capabilities of large-scale vision-language and multimodal foundation models.
You'll work on challenging research problems spanning model training, post-training, reinforcement learning, and multimodal reasoning. This is a hands-on role for someone who enjoys experimenting with cutting-edge approaches, improving model performance, and translating research breakthroughs into real-world capabilities.
You'll have the opportunity to work across the model development lifecycle, from data and training strategies to evaluation and optimization, helping push the boundaries of what multimodal AI systems can understand and accomplish.
What You'll Do
Multimodal Model Research: Research, develop, and improve vision-language models and multimodal foundation-model architectures.
Post-Training & Reinforcement Learning: Design and implement advanced training strategies, including supervised fine-tuning, preference optimization, and reinforcement learning, to improve model capabilities.
Model Performance & Optimization: Investigate approaches to improve reasoning, generalization, reliability, and training efficiency.
Data Quality & Training: Develop strategies for data curation, filtering, and synthetic data generation to improve training outcomes.
Evaluation & Benchmarking: Design experiments, evaluation frameworks, and benchmarks to measure model performance, identify failure modes, and guide research priorities.
Large-Scale Experimentation: Work with distributed training infrastructure and large-scale datasets to support research and model development.
Research Innovation: Explore emerging approaches in multimodal learning, model alignment, and foundation-model training.
What You Bring
Must Have
Hands-on experience researching, training, fine-tuning, or post-training large-scale foundation models, particularly vision-language or multimodal models.
Strong understanding of deep learning architectures, optimization techniques, and modern model training methodologies.
Practical experience with supervised fine-tuning (SFT), preference optimization, or reinforcement learning approaches such as DPO, GRPO, PPO, or RLHF.
Strong proficiency in Python and PyTorch, JAX, or comparable deep learning frameworks.
Experience designing, executing, and analyzing large-scale machine learning experiments.
Familiarity with distributed training systems and GPU-based model development.
Strong research instincts, analytical problem-solving skills, and the ability to independently drive complex technical projects.
Experience working with open-weight multimodal foundation models.
Research publications on top-tier journals/conferences, open-source contributions, or experience within leading AI research organizations.
Nice to Have
Experience with large-scale model post-training and reinforcement learning for reasoning or alignment.
Familiarity with multimodal data pipelines involving images, video, or other sensory inputs.
Experience with reward modeling, synthetic data generation, or advanced model evaluation.
Experience improving model capabilities through innovations in training strategies, data quality, or model architecture.
Standard company text repeated across Mecka AI's postings is omitted here.