Senior ML-engineer (portfolio asset allocation)

What You Will Be Doing:

• Solving the "Optimal Asset Allocation" problem.
• Conducting research and testing state-of-the-art (SOTA) algorithms and approaches for this task.
• Implementing and deploying the most effective algorithms into production.

Candidate Requirements:

• At least 6 years of professional Python development experience.
• 5 years of experience in the Data Science (DS) or Machine Learning Engineering (MLE) field.
• Proficiency with the standard MLE/DS Python stack, including Pandas, NumPy, PyTorch, etc.
• A minimum of 1 year of experience working on the Optimal Asset Allocation problem, with knowledge of SOTA solutions.
• Proven experience deploying models into production.
• A degree in computer science, applied mathematics, or a related field.
• Strong knowledge of various mathematical disciplines.
• English proficiency at B2 level or above.

Preferred Qualifications:

• Research experience or publications related to trading or Optimal Asset Allocation.
• Experience working with smart contracts on blockchain.
• Knowledge of liquidity pool and decentralized exchange (DEX) mechanisms.

What We Offer:

• Participation in the development of a fast-evolving product operating in real-time markets.
• Competitive salary based on interview results and qualifications, ranging from $6,000 to $14,000.
• Opportunities to expand your expertise by working with top-tier colleagues and learning on the job.
• A dynamic and motivated team of professionals focused on results. We value integrity, honesty, and openness.
• English language classes with a native speaker, health insurance after the probation period, and thoughtful holiday gifts.
• A chance to implement bold and ambitious initiatives.
• A flat organizational structure with no bureaucracy or "big boss" mentality.
• A results-oriented culture offering flexible schedules and fully remote work.

If this sounds like you, apply now to join our team!