Qureos Mentor

Meril

<div>
 
 
 Software Developer &ndash; Surgical Robotics
 
 
 
 
 Location:
 
 Vapi, Gujarat, India (On-site).
 
 
 
 Job Overview
 
 
 
 We are seeking a highly skilled
 
 Software Developer
 
 to
 
 design and develop advanced software control systems for surgical robotics
 
 . This role involves
 
 software architecture, real-time system development, and technical project management
 
 , working closely with
 
 cross-functional teams
 
 to integrate hardware, software, and robotic platforms.
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 
 Develop software systems
 
 for surgical robotics, ensuring compliance with
 
 medical device standards
 
 .
 </li>
 <li>
 
 Design and implement
 
 software applications and control algorithms using
 
 C#, WPF
 
 for real-time, safety-critical environments.
 </li>
 <li>
 
 Integrate software
 
 with electronics, mechanical systems, and robotic platforms, collaborating with
 
 hardware, firmware, and control engineers
 
 .
 </li>
 <li>
 
 Evaluate new technologies and architectures
 
 .
 </li>
 <li>
 Work closely with
 
 regulatory and quality assurance teams
 
 to meet
 
 IEC 62304, ISO 13485, and CE / FDA medical software regulations
 
 .
 </li>
 </ul>
 
 
 Required Qualifications &amp; Experience
 
 
 
 ✔ Proven experience in
 
 surgical robotics or robotic software development
 
 within a
 
 high-tech environment
 
 .
 
 
 ✔ Strong
 
 Object-Oriented Programming
 
 skills in
 
 C#, WPF.
 
 
 
 ✔ Expertise in
 
 robotics principles
 
 (kinematics, dynamics, control theory) and experience with Robot Operating System (ROS),
 
 communication protocols
 
 .
 
 
 ✔ Experience working with
 
 Real-Time Operating Systems (RTOS)
 
 for high-performance robotic applications.
 
 
 ✔ Strong
 
 problem-solving skills
 
 and ability to work in a
 
 fast-paced, dynamic environment
 
 .
 
 
 
 Skills &amp; Personal Qualities
 
 
 
 ✅ Ability to work in a
 
 fast-paced and dynamic environment
 
 .
 
 
 ✅ Strong desire to
 
 push for continuous improvement
 
 and
 
 deliver high-quality software
 
 .
 
 
 ✅ Excellent
 
 technical ability
 
 and
 
 personal communication skills
 
 to collaborate across teams.
 
 
 
 Preferred Qualifications &amp; Experience:
 
 
 
 ➤ Experience in
 
 medical device software development
 
 , adhering to
 
 IEC 62304, ISO 13485, and other regulatory standards
 
 .
 
 
 ➤ Background in
 
 technology consulting
 
 or working on
 
 multi-disciplinary robotics projects
 
 .
 
 
 ➤
 
 BE/ME/BTech/MTech
 
 with 3 years of experience in
 
 Computer Science, Robotics, or a related engineering field
 
 .
 
 
 
</div>

Software Developer

<div>
 
 As a
 
 Quantitative Machine Learning Engineer
 
 at
 
 Merli
 
 , you will help shape the next generation of
 
 AI-driven trading infrastructure
 
 . This role sits at the intersection of
 
 quantitative research, applied ML, and agentic system design
 
 , with the goal of optimizing high-frequency (HFT), medium-frequency (MFT), and wholesale trading strategies.
 
 
 You&rsquo;ll architect
 
 adaptive, agent-based ML systems
 
 that learn from evolving market microstructures, build robust forecasting and optimization models, and work with trading and infrastructure teams to deploy these solutions in
 
 real-world, low-latency environments
 
 .
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 
 Design &amp; Build Agentic ML Systems:
 
 Develop autonomous and semi-autonomous agents that perform data acquisition, alpha discovery, backtesting, and execution optimization.
 </li>
 <li>
 
 End-to-End ML Engineering:
 
 Architect, train, and deploy ML pipelines for HFT/MFT and wholesale trading, from signal generation to execution integration.
 </li>
 <li>
 
 Quantitative Research Integration:
 
 Collaborate with quant researchers to translate theoretical models into production-ready predictive and optimization systems.
 </li>
 <li>
 
 Market Forecasting:
 
 Develop deep learning, time series, and reinforcement learning models for price movement prediction and regime detection.
 </li>
 <li>
 
 Trading Optimization:
 
 Build reinforcement and meta-learning frameworks that adaptively tune strategy parameters in live environments.
 </li>
 <li>
 
 Scalable ML Infrastructure:
 
 Implement real-time inference, model versioning, and continuous learning pipelines for production systems.
 </li>
 <li>
 
 Performance Evaluation:
 
 Rigorously validate models with historical and synthetic simulations, ensuring robustness, latency, and financial soundness.
 </li>
 <li>
 
 Documentation &amp; Collaboration:
 
 Maintain high standards of reproducibility, version control, and code documentation across research and deployment layers.
 </li>
 </ul>
 
 
 What You&rsquo;ll Gain
 
 
 <ul>
 <li>
 Work at the frontier of
 
 AI, quantitative finance, and agentic automation
 
 .
 </li>
 <li>
 Collaborate with
 
 quant researchers, data engineers, and trading teams
 
 shaping next-gen trading systems.
 </li>
 <li>
 Exposure to
 
 meta-optimization frameworks
 
 ,
 
 reinforcement learning
 
 , and
 
 multi-agent orchestration
 
 .
 </li>
 <li>
 Hands-on experience with
 
 low-latency ML deployment
 
 , GPU acceleration, and distributed training in real trading environments.
 </li>
 <li>
 Ownership of models that directly influence
 
 market-making, forecasting, and strategy execution
 
 .
 </li>
 <li>
 Continuous learning and experimentation in a
 
 research-first, innovation-driven
 
 environment.
 </li>
 </ul>
 
 
 Qualifications
 
 
 <ul>
 <li>
 Bachelor&rsquo;s, Master&rsquo;s, or Ph.D. in Computer Science, Applied Mathematics, Financial Engineering, or a related quantitative field.
 </li>
 <li>
 
 3+ years
 
 of experience developing and deploying ML models in production (preferably in finance, trading, or large-scale decision systems).
 </li>
 <li>
 Strong proficiency in
 
 Python
 
 and ML frameworks:
 
 PyTorch, TensorFlow, scikit-learn, NumPy, Pandas
 
 .
 </li>
 <li>
 Deep understanding of
 
 supervised, unsupervised, and reinforcement learning
 
 ,
 
 time-series modeling
 
 , and
 
 probabilistic forecasting
 
 .
 </li>
 <li>
 Experience building
 
 scalable data pipelines
 
 with
 
 Kafka, Flink, or Ray
 
 and deploying models in
 
 Docker/Kubernetes
 
 environments.
 </li>
 <li>
 Knowledge of
 
 market microstructure
 
 ,
 
 portfolio optimization
 
 , or
 
 signal-based trading systems
 
 is highly desirable.
 </li>
 <li>
 Familiarity with
 
 meta-learning
 
 ,
 
 agent-based system design
 
 , or
 
 multi-agent coordination
 
 is a strong plus.
 </li>
 <li>
 Solid analytical, programming, and debugging skills with an emphasis on
 
 system reliability and latency optimization
 
 .
 </li>
 </ul>
 
 
 Preferred Technical Stack
 
 
 <ul>
 <li>
 
 Languages:
 
 Python, C++, Rust
 </li>
 <li>
 
 ML Infrastructure:
 
 Ray, MLflow, Airflow, Weights &amp; Biases
 </li>
 <li>
 
 Data Systems:
 
 Kafka, Redpanda, Redis, QuestDB
 </li>
 <li>
 
 Model Deployment:
 
 Triton Inference Server, TorchServe, or custom GPU inference
 </li>
 <li>
 
 Cloud/Hybrid Setup:
 
 Kubernetes, ArgoCD, Helm
 </li>
 </ul>
 
 
</div>

Quantitative ML Engineer

<div>
 
 Join our team as a
 
 Regulatory Documentation Specialist
 
 focused on
 
 IVF buffer media and sterile life science products
 
 . The ideal candidate will have strong expertise in
 
 regulatory compliance &amp; documentation.
 
 
 
 
 
 
 
 Qualifications:
 
 
 
 🎓 Master&rsquo;s in Biology / Biotechnology / Life Sciences
 
 
 🧾 3&ndash;5 years&rsquo; experience in regulatory documentation for sterile or IVF-related products
 
 
 
 
 
 
 Key Skills:
 
 
 
 ✅ DCGI submissions &amp; Product/ Site Master Files
 
 
 ✅ ISO 13485:2016 QMS documentation
 
 
 ✅ CE marking, MDR/IVDR compliance
 
 
 ✅ Knowledge of Drugs &amp; Cosmetics Act, Medical Device Rules (2017)
 
 
 ✅ Knowledge of
 
 WHO-GMP
 
 standards.
 
 
 
 
 
 
 Responsibilities:
 
 
 
 📄 Prepare and maintain regulatory dossiers, technical files &amp; SOPs
 
 
 🤝 Collaborate with QA, RA &amp; R&amp;D for submissions
 
 
 🔍 Support audits, product registrations &amp; renewals
 
 
 
 
 
 Kindly mail your update resume on
 
 vaishnavi.kadam@merillife.com
 
 
 
 
</div>

IVF Documentation

<div>
 
 
 About the Role
 
 
 
 As a
 
 Quantitative Data Engineer
 
 , you will be the backbone of the data ecosystem powering our
 
 quantitative research, trading, and AI-driven strategies
 
 . You will design, build, and maintain the
 
 high-performance data infrastructure
 
 that enables low-latency, high-fidelity access to market, fundamental, and alternative data across multiple asset classes.
 
 
 This role bridges
 
 quant engineering, data systems, and research enablement
 
 , ensuring that our researchers and traders have fast, reliable, and well-documented datasets for analysis and live trading. You&rsquo;ll be part of a cross-functional team working at the intersection of
 
 finance, machine learning, and distributed systems
 
 .
 
 
 
 Responsibilities
 
 
 <ul>
 <li>
 
 Architect and maintain scalable ETL pipelines
 
 for ingesting and transforming terabytes of structured, semi-structured, and unstructured market and alternative data.
 </li>
 <li>
 
 Design time-series optimized data stores
 
 and
 
 streaming frameworks
 
 to support low-latency data access for both backtesting and live trading.
 </li>
 <li>
 
 Develop ingestion frameworks
 
 integrating vendor feeds (Bloomberg, Refinitiv, Polygon, Quandl, etc.), exchange data, and internal execution systems.
 </li>
 <li>
 
 Collaborate with quantitative researchers and ML teams
 
 to ensure data accuracy, feature availability, and schema evolution aligned with modeling needs.
 </li>
 <li>
 
 Implement data quality checks, validation pipelines, and version control mechanisms
 
 for all datasets.
 </li>
 <li>
 
 Monitor and optimize distributed compute environments
 
 (Spark, Flink, Ray, or Dask) for performance and cost efficiency.
 </li>
 <li>
 
 Automate workflows
 
 using orchestration tools (Airflow, Prefect, Dagster) for reliability and reproducibility.
 </li>
 <li>
 
 Establish best practices
 
 for metadata management, lineage tracking, and documentation.
 </li>
 <li>
 
 Contribute to internal libraries and SDKs
 
 for seamless data access by trading and research applications.
 </li>
 </ul>
 
 
 In Trading Firms, Data Engineers Typically:
 
 
 <ul>
 <li>
 Build
 
 real-time data streaming systems
 
 to capture market ticks, order books, and execution signals.
 </li>
 <li>
 Manage
 
 versioned historical data lakes
 
 for backtesting and model training.
 </li>
 <li>
 Handle
 
 multi-venue data normalization
 
 (different exchanges and instruments).
 </li>
 <li>
 Integrate
 
 alternative datasets
 
 (satellite imagery, news sentiment, ESG, supply-chain data).
 </li>
 <li>
 Work closely with
 
 quant researchers
 
 to convert raw data into
 
 research-ready features
 
 .
 </li>
 <li>
 Optimize pipelines for
 
 ultra-low latency
 
 where milliseconds can impact P&amp;L.
 </li>
 <li>
 Implement
 
 data observability frameworks
 
 to ensure uptime and quality.
 </li>
 <li>
 Collaborate with
 
 DevOps and infra engineers
 
 to scale storage, caching, and compute.
 </li>
 </ul>
 
 
 Tech Stack
 
 
 <ul>
 <li>
 
 Languages:
 
 Python, SQL, Scala, Go, Rust (optional for HFT pipelines)
 </li>
 <li>
 
 Data Processing:
 
 Apache Spark, Flink, Ray, Dask, Pandas, Polars
 </li>
 <li>
 
 Workflow Orchestration:
 
 Apache Airflow, Prefect, Dagster
 </li>
 <li>
 
 Databases &amp; Storage:
 
 PostgreSQL, ClickHouse, DuckDB, ElasticSearch, Redis
 </li>
 <li>
 
 Data Lakes:
 
 Delta Lake, Iceberg, Hudi, Parquet
 </li>
 <li>
 
 Streaming:
 
 Kafka, Redpanda, Pulsar
 </li>
 <li>
 
 Cloud &amp; Infra:
 
 AWS (S3, EMR, Lambda), GCP, Azure, Kubernetes
 </li>
 <li>
 
 Version Control &amp; Lineage:
 
 DVC, MLflow, Feast, Great Expectations
 </li>
 <li>
 
 Visualization / Monitoring:
 
 Grafana, Prometheus, Superset, DataDog
 </li>
 <li>
 
 Tools for Finance:
 
 kdb+/q (for tick data), InfluxDB, QuestDB
 </li>
 </ul>
 
 
 What You Will Gain
 
 
 <ul>
 <li>
 
 End-to-end ownership
 
 of core data infrastructure in a high-impact, mission-critical domain.
 </li>
 <li>
 Deep exposure to
 
 quantitative research workflows
 
 ,
 
 market microstructure
 
 , and
 
 real-time trading systems
 
 .
 </li>
 <li>
 
 Collaboration with elite quantitative researchers, traders, and ML scientists.
 
 </li>
 <li>
 Hands-on experience with
 
 cutting-edge distributed systems
 
 and
 
 time-series data technologies
 
 .
 </li>
 <li>
 A culture that emphasizes
 
 technical excellence, autonomy, and experimentation.
 
 </li>
 </ul>
 
 
 Qualifications
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s in
 
 Computer Science, Data Engineering, or related field.
 
 </li>
 <li>
 
 2+ years
 
 of experience building and maintaining
 
 production-grade data pipelines
 
 .
 </li>
 <li>
 Proficiency in
 
 Python
 
 ,
 
 SQL
 
 , and frameworks like
 
 Airflow
 
 ,
 
 Spark
 
 , or
 
 Flink
 
 .
 </li>
 <li>
 Familiarity with
 
 cloud storage and compute (S3, GCS, EMR, Dataproc)
 
 and
 
 versioned data lakes (Delta, Iceberg)
 
 .
 </li>
 <li>
 Experience with
 
 financial datasets
 
 ,
 
 tick-level data
 
 , or
 
 high-frequency time series
 
 is a strong plus.
 </li>
 <li>
 Strong understanding of
 
 data modeling, schema design, and performance optimization
 
 .
 </li>
 <li>
 Excellent communication skills with an ability to support
 
 multidisciplinary teams
 
 .
 </li>
 </ul>
 
 
</div>

Data Engineer – Financial Infrastructure & Analytics

Join Meril 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.

Meril

ABOUT_COMPANY

Software Developer

Quantitative ML Engineer

IVF Documentation

Data Engineer – Financial Infrastructure & Analytics