We’re excited for you to be a part of our team

We are looking for experts in finance to work with our researchers to improve performance of AI models. We are looking for experts across a range of topics including investment banking, private equity, corporate finance, capital markets, portfolio management, research, trading, quant, accounting, and others. If you enjoy solving complex problems in finance and are interested in working with AI systems, please apply. No prior AI experience is required.

What does day-to-day look like:

• Evaluate LLM models for areas of finance where models do not perform well.
• Leverage your experience in finance to help AI learn about how to build models, conduct financial analyses, etc.
• Create rubrics to assess model capabilities on specific areas of your finance expertise (such as deal analysis, M&A assessments, and more).
• Collaborate with AI researchers and fellow finance experts to shape training methods, evaluation strategies, and benchmarks.

Requirements:

• 3+ years experience in Investment Banking, Private Equity, Capital Markets, Portfolio Management, Research, Trading, Quant, Venture Capital, Growth Equity, FP&A, Accounting, or Financial Consulting.
• Strong grasp of financial concepts (investment analysis, research, forecasting, revenue builds, corporate finance, asset management, risk management, etc.) based on your domain of expertise.
• Excellent English written communication.
  
  

AquSag is seeking a hands-on Machine Learning Senior Staff Engineer to lead cross-functional teams building and deploying cutting-edge LLM and ML systems. In this role, you’ll drive the full lifecycle of AI development, from research and large-scale model training to production deployment, while mentoring top engineers and collaborating closely with research and infrastructure leaders.  

You’ll combine technical depth in deep learning and MLOps with leadership in execution and strategy, ensuring that our AI initiatives deliver reliable, high-performance systems that translate research breakthroughs into measurable business impact.

This position is ideal for leaders who are still comfortable coding, optimizing large-scale training pipelines, building collab notebooks that break the models and navigating the intersection of research, engineering, and product delivery.

Roles & Responsibilities

• Lead and mentor a cross-functional team of ML engineers, data scientists, and MLOps professionals.
• Oversee the full lifecycle of LLM and ML projects — from data collection to training, evaluation, and deployment.
• Collaborate with Research, Product, and Infrastructure teams to define goals, milestones, and success metrics.
• Provide technical direction on large-scale model training, fine-tuning, and distributed systems design.
• Implement best practices in MLOps, model governance, experiment tracking, and CI/CD for ML.
• Manage compute resources, budgets, and ensure compliance with data security and responsible AI standards.
• Communicate progress, risks, and results to stakeholders and executives effectively.
• Overlap of 6 hours with PST time zone is mandatory.

Required Skills & Qualifications

• 9+ yrs of strong background in Machine Learning, NLP, and modern deep learning architectures (Transformers, LLMs).
• Hands-on experience with frameworks such as PyTorch, TensorFlow, Hugging Face, or DeepSpeed
• Hands-on experience in Docker for Production deployment. 
• Proven experience managing teams delivering ML/LLM models in production environments.
• Knowledge of distributed training, GPU/TPU optimization, and cloud platforms (AWS, GCP, Azure).
• Familiarity with MLOps tools like MLflow, Kubeflow, or Vertex AI for scalable ML pipelines.
• Excellent leadership, communication, and cross-functional collaboration skills.
• Bachelor’s or Master’s in Computer Science, Engineering, or related field (PhD preferred).

Nice to Have 

• Experience building Agentic applications 
• Experience training or fine-tuning foundation models.
• Contributions to open-source ML or LLM frameworks.
• Understanding of Responsible AI, bias mitigation, and model interpretability.

Offer Details:

• Commitments Required: 8 hours per day with overlap of 6 hours with PST.
• Employment type : Contractor assignment (no medical/paid leave)
• Duration of contract : 3 months (extendable up to 6 months based on performance and project needs)
• Location : LatAM, Europe, USA, Canada, Mexico, Africa
• Timezone : US PST (at least 6 hours overlap required)
• Payout: $40-$60 per hour (10% TDS applicable for Indian nationals)
  

Evaluation Process:

• 60 min Technical Interview
• Take Home Assessment 
• 60 min technical & cultural discussion

Location & Employment type: Remote & Contractual

Salary: Up to INR 1,20,000 per month

Experience: 4+ YoE

Experience: 9+ years overall with 2+ years leading ML/LLM teams

Location: Remote

Type: Contractual

Location: 6 – 10 years

Location: Bengaluru

Location: Bengaluru
Experience Required: 7-12 Years

Location: Remote & Contractual

Experience: 6+ Years